primary roots bacterial communities on WT plants grown in BX+ and BX- soils
Mapping ALL bacterial isolates to the BX maize root microbiota
Lisa Thönen
2023-08-31
File description
Background
(Hu et al. 2018, Nat. Comm).
Input
The analysis of the bacteria communities in R requires the following
input files:
- Design table: Database_S1.txt
- Count table: bacteria_DAT100.tab
- Taxonomy table: bacteria_TAXA100.tab
SetUp
Load the required packages and functions.
Design table
This is how the design table looks like:
## # A tibble: 3 × 24
## location days background genotype compartment root_type rep field_ID
## <fct> <chr> <fct> <fct> <fct> <chr> <dbl> <chr>
## 1 Changins 90 B73 WT rhizo no 3 48
## 2 Changins 90 no no soil no 4 S3
## 3 Changins 90 B73 bx1 root no 4 65
## # ℹ 16 more variables: DNA_extract_ID <chr>, MiSeq_bac <chr>,
## # padding_seq_bac <chr>, bc_799F_ID <chr>, bc_799F_seq <chr>,
## # bc_1193R_ID <chr>, bc_1193R_seq <chr>, sample_ID_bac <chr>,
## # MiSeq_fungi <chr>, padding_seq_fun <chr>, bc_ITS1F_ID <chr>,
## # bc_ITS1F_seq <chr>, bc_ITS2_ID <chr>, bc_ITS2_seq <chr>,
## # sample_ID_fun <chr>, groups <fct>Count table
## # A tibble: 6 × 24
## location days background genotype compartment root_type rep field_ID
## <fct> <chr> <fct> <fct> <fct> <chr> <dbl> <chr>
## 1 Changins 90 B73 WT rhizo no 3 48
## 2 Changins 90 no no soil no 4 S3
## 3 Changins 90 B73 bx1 root no 4 65
## 4 Changins 90 B73 WT root no 3 48
## 5 Changins 90 B73 WT root no 5 97
## 6 Changins 90 no no soil no 3 S2
## # ℹ 16 more variables: DNA_extract_ID <chr>, MiSeq_bac <chr>,
## # padding_seq_bac <chr>, bc_799F_ID <chr>, bc_799F_seq <chr>,
## # bc_1193R_ID <chr>, bc_1193R_seq <chr>, sample_ID_bac <chr>,
## # MiSeq_fungi <chr>, padding_seq_fun <chr>, bc_ITS1F_ID <chr>,
## # bc_ITS1F_seq <chr>, bc_ITS2_ID <chr>, bc_ITS2_seq <chr>,
## # sample_ID_fun <chr>, groups <fct>This is how the count table looks like:
## BACT10_sheffield BACT11_sheffield BACT12_sheffield BACT13_sheffield
## ASV1 0 0 0 0
## ASV2 0 0 0 0
## ASV3 0 0 0 0
## ASV4 0 0 0 0
## ASV5 718 316 928 1297
## BACT14_sheffield
## ASV1 0
## ASV2 0
## ASV3 0
## ASV4 0
## ASV5 1343Taxonomy table
This is how the taxonomy table looks like:
## phylum order genus
## ASV1 Proteobacteria Pseudomonadales Pseudomonas
## ASV2 Proteobacteria Betaproteobacteriales Pelomonas
## ASV3 Proteobacteria Sphingomonadales Sphingobium
## ASV4 Proteobacteria Pseudomonadales Pseudomonas
## ASV5 Firmicutes Bacillales BacillusFeedback experiment
The field experiment consisted of a total of 20 samples representing 2 sample groups (WT roots in BX+ and BX- soils). The number of replicates for all sample groups is given below.
Experimental design
| groups_genotype_compartment_location_background_root_type | Samples |
|---|---|
| bx1_rhizo_Changins_B73_no | 7 |
| bx1_rhizo_Ithaca_W22_no | 8 |
| bx1_rhizo_Zurich_B73_no | 12 |
| bx1_rhizo_Zurich_W22_no | 12 |
| bx1_root_Changins_B73_no | 7 |
| bx1_root_Ithaca_W22_no | 7 |
| bx1_root_Sheffield_W22_crown | 8 |
| bx1_root_Sheffield_W22_primary | 8 |
| bx1_root_Zurich_B73_no | 12 |
| bx1_root_Zurich_W22_no | 12 |
| bx1_soil_Ithaca_W22_no | 8 |
| bx1_soil_Zurich_B73_no | 12 |
| bx1_soil_Zurich_W22_no | 12 |
| bx2_rhizo_Ithaca_W22a_no | 8 |
| bx2_root_Ithaca_W22a_no | 6 |
| bx2_root_Sheffield_W22a_crown | 8 |
| bx2_root_Sheffield_W22a_primary | 8 |
| bx2_soil_Ithaca_W22a_no | 8 |
| bx6_rhizo_Ithaca_W22_no | 8 |
| bx6_root_Ithaca_W22_no | 8 |
| bx6_root_Sheffield_W22_crown | 8 |
| bx6_root_Sheffield_W22_primary | 8 |
| bx6_soil_Ithaca_W22_no | 8 |
| no_soil_Changins_no_no | 10 |
| no_soil_Sheffield_no_no | 8 |
| WT_rhizo_Changins_B73_no | 10 |
| WT_rhizo_Ithaca_W22_no | 8 |
| WT_rhizo_Zurich_B73_no | 11 |
| WT_rhizo_Zurich_W22_no | 6 |
| WT_root_Changins_B73_no | 10 |
| WT_root_Ithaca_W22_no | 6 |
| WT_root_Sheffield_W22_crown | 8 |
| WT_root_Sheffield_W22_primary | 8 |
| WT_root_Zurich_B73_no | 11 |
| WT_root_Zurich_W22_no | 6 |
| WT_soil_Ithaca_W22_no | 8 |
| WT_soil_Zurich_B73_no | 11 |
| WT_soil_Zurich_W22_no | 6 |
## data normalization
# total sum as %
bDAT_norm <- t(t(bDAT)/colSums(bDAT)) * 100
bDAT_norm <- bDAT_norm[rowSums(bDAT_norm) > 0,]
# dim(bDAT_norm)
# rarefication with library(vegan)
set.seed(3920) # 3920 = zip code of Zermatt with lovely Matterhorn
bDAT_rare <- t(vegan::rrarefy(t(bDAT), min(colSums(bDAT_norm))))
## Phyloseq object
# library(phyloseq)
# library(ggplot2)
# library(plyr)
all_phy <- phyloseq(sample_data(design),
otu_table(bDAT_norm, taxa_are_rows=T),
tax_table(as.matrix(bTAX[rownames(bDAT_norm),])) )all_phy_psmelt <- psmelt(all_phy)dir.create("../Output/II_Field_soils", recursive = T, showWarnings = F)
#write_rds(design, "../Output/II_Field_soils/design.rds")
#write_rds(bDAT_norm, "../Output/II_Field_soils/bDAT_norm.rds")
#write_rds(all_phy_psmelt, "../Output/II_Field_soils/all_phy_psmelt.rds")Mapping bacterial isolates to microbiota members
# ### uploading isolate-OTU assignments
iso.tab <- read.csv("../Input/II_Field_soils/hits97_field.csv")
colnames(iso.tab) <- c("nr", "ASV", "Strain", "%")
iso.tab$Strain <- gsub("_27f", "", iso.tab$Strain)
iso.tab$Strain <- gsub("_1492r", "", iso.tab$Strain)LMX92 & LMX9231 were in the wrong direction in the sequences used for the mapping, but they are almost 100 % similar to LME3, therefore it will be the same mapping result.
LME3 <- iso.tab %>% filter(Strain %in% "LME3")
LMX92 <- LME3 %>% mutate(Strain = gsub("LME3", "LMX92", Strain))
LMX9231 <- LME3 %>% mutate(Strain = gsub("LME3", "LMX9231", Strain))
iso.tab <- rbind(iso.tab, LMX9231, LMX92)iso.tab %<>% filter(!Strain %in% c("LAT1", "LBH1", "LBH4", "LBH6", "LTA5", "LWH2", "LWH6", "LWO4", NA))
head(iso.tab) %>% pander()| nr | ASV | Strain | % |
|---|---|---|---|
| 1 | ASV1 | LMX11 | 1 |
| 2 | ASV1 | LMX4 | 1 |
| 3 | ASV1 | LMX9 | 1 |
| 11 | ASV1 | LBN5 | 1 |
| 12 | ASV1 | LMS3 | 1 |
| 14 | ASV1 | LPD11 | 0.9974 |
iso.tab <- iso.tab %>% dplyr::select("%", "Strain", "ASV")
iso_names <- names(table(iso.tab$ASV))[-1]
#write_rds(iso.tab, "../Output/II_Field_soils/iso.tab.rds")
#write_rds(iso_names, "../Output/II_Field_soils/iso_names.rds")# design <- read_rds("design.rds")
# bDAT_norm <- read_rds("bDAT_norm.rds")
# all_phy_psmelt <- read_rds("all_phy_psmelt.rds")
# iso_names <- read_rds("iso_names.rds")CHANGINS B73
Root bacterial communities on WT plants grown in BX+ and BX- soils
The 50 most abundant ZOTUs in the root compartment are presented in the rank abundance plot below.
Rhizosphere bacterial communities on WT plants grown in BX+ and BX- soils
Isolates mapped to microbiome
Isolates in root microbiome
strain_col <- rep("black", length(rownames(bDAT_norm_root_Ch_MEANs)))
names(strain_col) <- rownames(bDAT_norm_root_Ch_MEANs)
strain_col <- ifelse(names(strain_col) %in% iso_names, "dodgerblue3","lightgrey")Supplementary figure 600 x 1600
## rank abundance plot
# postscript("Field_rhizo_profile_norm_MEANs_bacteria.eps", paper="special", width=7, height=5, horizontal = FALSE)
# par(mar=c(11,4,4,4), oma=c(0,0,0,0))
# pdf("LAC11_is_ZOTU3257.pdf", height=4, width=5)
p <- barplot(t(bDAT_norm_root_Ch_MEANs)[,1:100], border=NA,
col=c("gold2","palegreen3"), beside=T, las=2, ylim=c(0, 6),
cex.names=.75, main = "Changins roots",
ylab=paste("relative abundance [%]",sep=" ") , xaxt="n")
# source("functions/staxlab.R")
staxlab(side=1, at=(p[1,]+p[2,])/2, labels=rownames(bDAT_norm_root_Ch_MEANs)[1:100], col=strain_col[1:100], srt=45, cex=1)
# legend
legend(x="topright", legend=colnames(bDAT_norm_root_Ch_MEANs), col=c("gold2","palegreen3"), bty="n", xpd=TRUE, inset=c(0,0), pch=19, cex=1)
# error bars
arrows(x0=p, y0=t(bDAT_norm_root_Ch_MEANs)[,1:100], y1=t(bDAT_norm_root_Ch_MEANs)[,1:100] + t(bDAT_norm_root_WT_Ch_SEs)[,1:100], angle=90, length=0.02, lwd=1)
# stats
# stats_mw <- ifelse(rownames(bDAT_norm_rhizo_Ch_MEANs) %in% field_rhizo_lrt_OTUs, "*","")
# text(y=(apply(bDAT_norm_rhizo_Ch_MEANs, 1, max)*1.75)[1:100], x=((p[1,] + p[2,])/2)[1:100], labels=stats_mw[1:100])
# dev.off()Isolates in Rhizosphere microbiome
strain_col_rhizo <- rep("black", length(rownames(bDAT_norm_rhizo_Ch_MEANs)))
names(strain_col_rhizo) <- rownames(bDAT_norm_rhizo_Ch_MEANs)
strain_col_rhizo <- ifelse(names(strain_col_rhizo) %in% iso_names, "dodgerblue3","lightgrey")
RECKENHOLZ B73
Root bacterial communities on WT plants grown in BX+ and BX- soils
The 50 most abundant ZOTUs in the root compartment are presented in the rank abundance plot below.
Rhizosphere bacterial communities on WT plants grown in BX+ and BX- soils
Isolates mapped to microbiome
Isolates in root microbiome
strain_col <- rep("black", length(rownames(bDAT_norm_root_Zh_MEANs)))
names(strain_col) <- rownames(bDAT_norm_root_Zh_MEANs)
strain_col <- ifelse(names(strain_col) %in% iso_names, "dodgerblue3","lightgrey")## rank abundance plot
# postscript("Field_rhizo_profile_norm_MEANs_bacteria.eps", paper="special", width=7, height=5, horizontal = FALSE)
# par(mar=c(11,4,4,4), oma=c(0,0,0,0))
# pdf("LAC11_is_ZOTU3257.pdf", height=4, width=5)
p <- barplot(t(bDAT_norm_root_Zh_MEANs)[,1:100], border=NA,
col=c("gold2","palegreen3"), beside=T, las=2, ylim=c(0, 20),
cex.names=.75, main = "Zurich B73 roots",
ylab=paste("relative abundance [%]",sep=" ") , xaxt="n")
# source("functions/staxlab.R")
staxlab(side=1, at=(p[1,]+p[2,])/2, labels=rownames(bDAT_norm_root_Zh_MEANs)[1:100], col=strain_col[1:100], srt=45, cex=1)
# legend
legend(x="topright", legend=colnames(bDAT_norm_root_Zh_MEANs), col=c("gold2","palegreen3"), bty="n", xpd=TRUE, inset=c(0,0), pch=19, cex=1)
# error bars
arrows(x0=p, y0=t(bDAT_norm_root_Zh_MEANs)[,1:100], y1=t(bDAT_norm_root_Zh_MEANs)[,1:100] + t(bDAT_norm_root_Zh_SEs)[,1:100], angle=90, length=0.02, lwd=1)
# stats
# stats_mw <- ifelse(rownames(bDAT_norm_rhizo_Zh_MEANs) %in% field_rhizo_lrt_OTUs, "*","")
# text(y=(apply(bDAT_norm_rhizo_Zh_MEANs, 1, max)*1.75)[1:100], x=((p[1,] + p[2,])/2)[1:100], labels=stats_mw[1:100])
# dev.off()Isolates in Rhizosphere microbiome
strain_col_rhizo <- rep("black", length(rownames(bDAT_norm_rhizo_Zh_MEANs)))
names(strain_col_rhizo) <- rownames(bDAT_norm_rhizo_Zh_MEANs)
strain_col_rhizo <- ifelse(names(strain_col_rhizo) %in% iso_names, "dodgerblue3","lightgrey")
RECKENHOLZ W22
Root bacterial communities on WT plants grown in BX+ and BX- soils
The 50 most abundant ZOTUs in the root compartment are presented in the rank abundance plot below.
Rhizosphere bacterial communities on WT plants grown in BX+ and BX- soils
Isolates mapped to microbiome
Isolates in root microbiome
strain_col <- rep("black", length(rownames(bDAT_norm_root_Zh_22_MEANs)))
names(strain_col) <- rownames(bDAT_norm_root_Zh_22_MEANs)
strain_col <- ifelse(names(strain_col) %in% iso_names, "dodgerblue3","lightgrey")## rank abundance plot
# postscript("Field_rhizo_profile_norm_MEANs_bacteria.eps", paper="special", width=7, height=5, horizontal = FALSE)
# par(mar=c(11,4,4,4), oma=c(0,0,0,0))
# pdf("LAC11_is_ZOTU3257.pdf", height=4, width=5)
p <- barplot(t(bDAT_norm_root_Zh_22_MEANs)[,1:100], border=NA,
col=c("gold2","palegreen3"), beside=T, las=2, ylim=c(0, 30),
cex.names=.75, main = "Zurich W22 roots",
ylab=paste("relative abundance [%]",sep=" ") , xaxt="n")
# source("functions/staxlab.R")
staxlab(side=1, at=(p[1,]+p[2,])/2, labels=rownames(bDAT_norm_root_Zh_22_MEANs)[1:100], col=strain_col[1:100], srt=45, cex=1)
# legend
legend(x="topright", legend=colnames(bDAT_norm_root_Zh_22_MEANs), col=c("gold2","palegreen3"), bty="n", xpd=TRUE, inset=c(0,0), pch=19, cex=1)
# error bars
arrows(x0=p, y0=t(bDAT_norm_root_Zh_22_MEANs)[,1:100], y1=t(bDAT_norm_root_Zh_22_MEANs)[,1:100] + t(bDAT_norm_root_Zh_22_SEs)[,1:100], angle=90, length=0.02, lwd=1)
# stats
# stats_mw <- ifelse(rownames(bDAT_norm_rhizo_Zh_22_MEANs) %in% field_rhizo_lrt_OTUs, "*","")
# text(y=(apply(bDAT_norm_rhizo_Zh_22_MEANs, 1, max)*1.75)[1:100], x=((p[1,] + p[2,])/2)[1:100], labels=stats_mw[1:100])
# dev.off()Isolates in Rhizosphere microbiome
strain_col_rhizo <- rep("black", length(rownames(bDAT_norm_rhizo_Zh_22_MEANs)))
names(strain_col_rhizo) <- rownames(bDAT_norm_rhizo_Zh_22_MEANs)
strain_col_rhizo <- ifelse(names(strain_col_rhizo) %in% iso_names, "dodgerblue3","lightgrey")
AURORA W22
Root bacterial communities on WT plants grown in BX+ and BX- soils
The 50 most abundant ZOTUs in the root compartment are presented in the rank abundance plot below.
Rhizosphere bacterial communities on WT plants grown in BX+ and BX- soils
Isolates mapped to microbiome
Isolates in root microbiome
strain_col <- rep("black", length(rownames(bDAT_norm_root_Au_22_MEANs)))
names(strain_col) <- rownames(bDAT_norm_root_Au_22_MEANs)
strain_col <- ifelse(names(strain_col) %in% iso_names, "dodgerblue3","lightgrey")## rank abundance plot
# postscript("Field_rhizo_profile_norm_MEANs_bacteria.eps", paper="special", width=7, height=5, horizontal = FALSE)
# par(mar=c(11,4,4,4), oma=c(0,0,0,0))
# pdf("LAC11_is_ZOTU3257.pdf", height=4, width=5)
p <- barplot(t(bDAT_norm_root_Au_22_MEANs)[,1:100], border=NA,
col=c("gold2","palegreen3"), beside=T, las=2, ylim=c(0, 8),
cex.names=.75, main = "Aurora W22 roots",
ylab=paste("relative abundance [%]",sep=" ") , xaxt="n")
# source("functions/staxlab.R")
staxlab(side=1, at=(p[1,]+p[2,])/2, labels=rownames(bDAT_norm_root_Au_22_MEANs)[1:100], col=strain_col[1:100], srt=45, cex=1)
# legend
legend(x="topright", legend=colnames(bDAT_norm_root_Au_22_MEANs), col=c("gold2","palegreen3"), bty="n", xpd=TRUE, inset=c(0,0), pch=19, cex=1)
# error bars
arrows(x0=p, y0=t(bDAT_norm_root_Au_22_MEANs)[,1:100], y1=t(bDAT_norm_root_Au_22_MEANs)[,1:100] + t(bDAT_norm_root_Au_22_SEs)[,1:100], angle=90, length=0.02, lwd=1)
# stats
# stats_mw <- ifelse(rownames(bDAT_norm_rhizo_Au_22_MEANs) %in% field_rhizo_lrt_OTUs, "*","")
# text(y=(apply(bDAT_norm_rhizo_Au_22_MEANs, 1, max)*1.75)[1:100], x=((p[1,] + p[2,])/2)[1:100], labels=stats_mw[1:100])
# dev.off()Isolates in Rhizosphere microbiome
strain_col_rhizo <- rep("black", length(rownames(bDAT_norm_rhizo_Au_22_MEANs)))
names(strain_col_rhizo) <- rownames(bDAT_norm_rhizo_Au_22_MEANs)
strain_col_rhizo <- ifelse(names(strain_col_rhizo) %in% iso_names, "dodgerblue3","lightgrey")
SHEFFIELD W22
Root bacterial communities on WT plants grown in BX+ and BX- soils
The 50 most abundant ZOTUs in the root compartment are presented in the rank abundance plot below.
Crown roots bacterial communities on WT plants grown in BX+ and BX- soils
Isolates mapped to microbiome
Isolates in root microbiome
strain_col <- rep("black", length(rownames(bDAT_norm_root_Sh_22_MEANs)))
names(strain_col) <- rownames(bDAT_norm_root_Sh_22_MEANs)
strain_col <- ifelse(names(strain_col) %in% iso_names, "dodgerblue3","lightgrey")## rank abundance plot
# postscript("Field_Crown_profile_norm_MEANs_bacteria.eps", paper="special", width=7, height=5, horizontal = FALSE)
# par(mar=c(11,4,4,4), oma=c(0,0,0,0))
# pdf("LAC11_is_ZOTU3257.pdf", height=4, width=5)
p <- barplot(t(bDAT_norm_root_Sh_22_MEANs)[,1:100], border=NA,
col=c("gold2","palegreen3"), beside=T, las=2, ylim=c(0, 2),
cex.names=.75, main = "Sheffield W22 roots",
ylab=paste("relative abundance [%]",sep=" ") , xaxt="n")
# source("functions/staxlab.R")
staxlab(side=1, at=(p[1,]+p[2,])/2, labels=rownames(bDAT_norm_root_Sh_22_MEANs)[1:100], col=strain_col[1:100], srt=45, cex=1)
# legend
legend(x="topright", legend=colnames(bDAT_norm_root_Sh_22_MEANs), col=c("gold2","palegreen3"), bty="n", xpd=TRUE, inset=c(0,0), pch=19, cex=1)
# error bars
arrows(x0=p, y0=t(bDAT_norm_root_Sh_22_MEANs)[,1:100], y1=t(bDAT_norm_root_Sh_22_MEANs)[,1:100] + t(bDAT_norm_root_Sh_22_MEANs)[,1:100], angle=90, length=0.02, lwd=1)
# stats
# stats_mw <- ifelse(rownames(bDAT_norm_Crown_Sh_22_MEANs) %in% field_Crown_lrt_OTUs, "*","")
# text(y=(apply(bDAT_norm_Crown_Sh_22_MEANs, 1, max)*1.75)[1:100], x=((p[1,] + p[2,])/2)[1:100], labels=stats_mw[1:100])
# dev.off()Isolates in Crownsphere microbiome
strain_col_Crown <- rep("black", length(rownames(bDAT_norm_Crown_Sh_22_MEANs)))
names(strain_col_Crown) <- rownames(bDAT_norm_Crown_Sh_22_MEANs)
strain_col_Crown <- ifelse(names(strain_col_Crown) %in% iso_names, "dodgerblue3","lightgrey")
Isolates in primarysphere microbiome
strain_col_primary <- rep("black", length(rownames(bDAT_norm_primary_Sh_22_MEANs)))
names(strain_col_primary) <- rownames(bDAT_norm_primary_Sh_22_MEANs)
strain_col_primary <- ifelse(names(strain_col_primary) %in% iso_names, "dodgerblue3","lightgrey")
Abundance psmelt
all_phy_psmelt_iso <- all_phy_psmelt %>% filter(root_type %in% c("no", "primary")) %>%
dplyr::select(OTU, phylum, family, genus, Abundance, location, background, genotype,
compartment) %>%
group_by(OTU, phylum, family, genus, location, background, genotype, compartment) %>%
dplyr::summarise(Abundace_mean = mean(Abundance)) %>%
dplyr::left_join(., iso.tab, by = c("OTU" = "ASV")) %>%
# dplyr::select(-`%`) %>%
unique()#write_rds(all_phy_psmelt_iso, "../Output/II_Field_soils/all_phy_psmelt_iso.rds")… stopped here… code has a problem Error: Problem with
mutate() input Changins_B73_WT_root_rank. x
Input Changins_B73_WT_root_rank can’t be recycled to size
1. i Input Changins_B73_WT_root_rank is
1:nrow(.). i Input Changins_B73_WT_root_rank
must be size 1, not 26571. i The error occurred in group 1: OTU =
“ASV1”, phylum = “Proteobacteria”, family = “Pseudomonadaceae”, genus =
“Pseudomonas”.
# all_phy_psmelt_iso_group_abundance_rank <- all_phy_psmelt_iso_group_abundance %>% as.data.frame() %>%
# dplyr::select(-Strain, -Ithaca_W22_bx6_soil, -Ithaca_W22_bx6_rhizo, -Ithaca_W22_bx6_root, -Ithaca_W22a_bx2_soil, -Ithaca_W22a_bx2_rhizo,
# -Ithaca_W22a_bx2_root, -Sheffield_W22_bx6_root, -Sheffield_W22a_bx2_root) %>%
# dplyr::arrange(desc(Changins_B73_WT_rhizo)) %>% mutate(Changins_B73_WT_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Changins_B73_WT_root)) %>% mutate(Changins_B73_WT_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Changins_B73_bx1_rhizo)) %>% mutate(Changins_B73_bx1_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Changins_B73_bx1_root)) %>% mutate(Changins_B73_bx1_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Ithaca_W22_WT_soil)) %>% mutate(Ithaca_W22_WT_soil_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Ithaca_W22_WT_rhizo)) %>% mutate(Ithaca_W22_WT_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Ithaca_W22_WT_root)) %>% mutate(Ithaca_W22_WT_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Ithaca_W22_bx1_soil)) %>% mutate(Ithaca_W22_bx1_soil_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Ithaca_W22_bx1_rhizo)) %>% mutate(Ithaca_W22_bx1_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Ithaca_W22_bx1_root)) %>% mutate(Ithaca_W22_bx1_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_B73_WT_soil)) %>% mutate(Zurich_B73_WT_soil_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_B73_WT_rhizo)) %>% mutate(Zurich_B73_WT_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_B73_WT_root)) %>% mutate(Zurich_B73_WT_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_B73_bx1_soil)) %>% mutate(Zurich_B73_bx1_soil_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_B73_bx1_rhizo)) %>% mutate(Zurich_B73_bx1_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_B73_bx1_root)) %>% mutate(Zurich_B73_bx1_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_W22_WT_soil)) %>% mutate(Zurich_W22_WT_soil_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_W22_WT_rhizo)) %>% mutate(Zurich_W22_WT_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_W22_WT_root)) %>% mutate(Zurich_W22_WT_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_W22_bx1_soil)) %>% mutate(Zurich_W22_bx1_soil_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_W22_bx1_rhizo)) %>% mutate(Zurich_W22_bx1_rhizo_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Zurich_W22_bx1_root)) %>% mutate(Zurich_W22_bx1_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Sheffield_no_no_soil)) %>% mutate(Sheffield_no_no_soil_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Sheffield_W22_WT_root)) %>% mutate(Sheffield_W22_WT_root_rank = 1:nrow(.)) %>%
# dplyr::arrange(desc(Sheffield_W22_bx1_root)) %>% mutate(Sheffield_W22_bx1_root_rank = 1:nrow(.))
#
# all_phy_psmelt_iso_group_abundance_rank_iso <- all_phy_psmelt_iso_group_abundance_rank %>%
# dplyr::left_join(., iso.tab, by = c("OTU" = "ZOTU")) %>% dplyr::select(-`%`) %>% unique()
#
# all_phy_psmelt_iso_group_abundance_rank <- all_phy_psmelt_iso_group_abundance_rank_iso %>%
# mutate(Isolate = case_when(Strain != "NA" ~ TRUE, Strain %in% NA ~ FALSE))# all_phy_psmelt_iso_group_abundance_rank_iso %>% dplyr::select(OTU, phylum, family, genus, BXp_feedback_WT_Root_Rank, BXm_feedback_WT_Root_Rank, Strain) %>% filter(Strain != "NA") %>% knitr::kable()# all_phy_psmelt_iso_group_abundance_rank %>% dplyr::select(OTU, phylum, family, genus, BXp_feedback_WT_Root_Rank, BXm_feedback_WT_Root_Rank, Isolate) %>% unique() %>% dplyr::arrange(BXp_feedback_WT_Root_Rank) %>% as.data.frame() %>% slice_head(n = 100) %>% knitr::kable() # write_rds(all_phy_psmelt_iso_group_abundance_rank_iso, "all_phy_psmelt_iso_group_abundance_rank_iso_Hu_et_al_FB.rds")
# write_rds(all_phy_psmelt_iso_group_abundance_rank, "all_phy_psmelt_iso_group_abundance_rank_Hu_et_al_FB.rds")BX colonization psmelt - read rds
# design <- read_rds("design.rds")
# bDAT_norm <- read_rds("bDAT_norm.rds")
# all_phy_psmelt <- read_rds("all_phy_psmelt.rds")
# iso.tab <- read_rds("iso.tab.rds")
# iso_names <- read_rds("iso_names.rds")BX abundance isolates
For MRB tree Fig. 1A and for correlations Fig 5A&B “all_phy_psmelt_iso_BX_abundance.rds”
# the computation of these two commands takes a lot of time and therefore the file is saved as rds and then read as rds back into R
# # select the columns and the root type
all_phy_psmelt_BX <- all_phy_psmelt %>% filter(root_type %in% c("no", "primary")) %>%
dplyr::select(OTU, Sample, rep, phylum, family, genus, Abundance, location, background,
genotype, compartment)
# Calculate BX colonization (WT/bx1 ratio and Log fold change (log2FC = log2(WT)-log2(bx1))) and join to isolates
all_phy_psmelt_iso_BX_abundance <- all_phy_psmelt_BX %>%
filter(OTU %in% iso_names) %>%
filter(genotype %in% c("WT", "bx1")) %>%
dplyr::select(-Sample) %>%
filter(OTU %in% iso_names) %>%
pivot_wider(names_from = 9, values_from = Abundance, values_fn = mean) %>%
mutate(WT = replace_na(WT, 0), bx1 = replace_na(bx1, 0)) %>%
mutate(BXcol = WT/bx1, log2FC = log2(WT)-log2(bx1), WTbx1dif = WT - bx1, WTbx1dif_zscore = bx1 - WT / sd(WT)) %>%
left_join(iso.tab, by = c("OTU" = "ASV")) %>%
dplyr::select(-`%`)
all_phy_psmelt_iso_BX <- all_phy_psmelt_BX %>%
filter(OTU %in% iso_names) %>%
filter(genotype %in% c("WT", "bx1")) %>%
dplyr::select(-Sample) %>%
filter(OTU %in% iso_names) %>%
left_join(iso.tab, by = c("OTU" = "ASV")) %>%
dplyr::select(-`%`)
# write rds
#write_rds(all_phy_psmelt_iso_BX_abundance, "../Output/II_Field_soils/all_phy_psmelt_iso_BX_abundance.rds")
#write_rds(all_phy_psmelt_BX, "../Output/II_Field_soils/all_phy_psmelt_BX.rds")# all_phy_psmelt_iso_BX_abundance <- read_rds("all_phy_psmelt_iso_BX_abundance.rds")
#
# all_phy_psmelt_BX_abundance <- read_rds("all_phy_psmelt_BX_abundance.rds")all_phy_psmelt_iso_BX_abundance_meanOTU <- all_phy_psmelt_iso_BX_abundance %>% group_by(OTU, family, location, background, compartment, Strain) %>% dplyr::summarize(WT_mean = mean(WT), bx1_mean = mean(bx1), BXcol_mean = mean(BXcol), log2FC_mean = mean(log2FC), WTbx1dif_mean = mean(WTbx1dif))
all_phy_psmelt_iso_BX_abundance_meanOTU$family <- gsub("Burkholderiaceae", "Oxalobacteraceae", all_phy_psmelt_iso_BX_abundance_meanOTU$family)
#write_rds(all_phy_psmelt_iso_BX_abundance_meanOTU, "../Output/II_Field_soils/all_phy_psmelt_iso_BX_abundance_meanOTU.rds")# all_phy_psmelt_iso_BX_abundance %>% ggplot(aes(x = OTU, y = log2FC)) +
# geom_point(aes(colour = family))# all_phy_psmelt_iso_BX_abundance_meanOTU %>%
# filter(!log2FC_OTU %in% c(-Inf, Inf, NA, NaN)) %>%
# ggplot(aes(x = OTU, y = log2FC_OTU)) +
# geom_point(aes(colour = family)) +
# facet_wrap(interaction(location, background) ~ compartment)# all_phy_psmelt_iso_BX_abundance %>%
# # filter(!log2FC_OTU %in% c(-Inf, Inf, NA, NaN)) %>%
# ggplot(aes(x = OTU, y = WTbx1dif)) +
# geom_point(aes(colour = family)) +
# facet_wrap(interaction(location, background) ~ compartment)all_phy_psmelt_iso_BX_abundance_meanOTU %>%
# filter(!log2FC_OTU %in% c(-Inf, Inf, NA, NaN)) %>%
filter(!WTbx1dif_mean %in% "0") %>%
ggplot(aes(x = OTU, y = WTbx1dif_mean)) +
geom_point(aes(colour = family)) +
facet_wrap(interaction(location, background) ~ compartment)
# all_phy_psmelt_iso_BX_abundance_meanOTU %>%
# filter(family %in% "Sphingomonadaceae") %>%
# filter(location %in% "Changins") %>%
# filter(!WTbx1dif_mean %in% 0) %>%
# unique() %>%
# # filter(!log2FC_OTU %in% c(-Inf, Inf, NA, NaN)) %>%
# ggplot(aes(x = OTU, y = WTbx1dif_mean)) +
# geom_point(aes(colour = WT_mean)) +
# facet_wrap(interaction(location, background) ~ compartment) +
# theme(axis.text.x=element_text(angle = 90, hjust = 0, vjust = 0.5)) # all_phy_psmelt_iso_BX_abundance_meanOTU %>%
# filter(location %in% "Changins") %>%
# # filter(!log2FC_OTU %in% c(-Inf, Inf, NA, NaN)) %>%
# ggplot(aes(x = OTU, y = log2FC_OTU)) +
# geom_point(aes(colour = family)) +
# facet_wrap(interaction(location, background) ~ compartment)# all_phy_psmelt_iso_BX_abundance %>%
# filter(location %in% "Changins") %>%
# # filter(!log2FC_OTU %in% c(-Inf, Inf, NA, NaN)) %>%
# ggplot(aes(x = OTU, y = log2FC)) +
# geom_point(aes(colour = family)) +
# facet_wrap(interaction(location, background) ~ compartment)# all_phy_psmelt_iso_BX_abundance %>% filter(log2FC %in% c(-Inf, Inf, NA, NaN))# all_phy_psmelt_iso_BX_abundance %<>% as.data.frame() %>% dplyr::mutate(WT = replace_na(WT, 0))
#
# all_phy_psmelt_iso_BX_abundance_cum <- all_phy_psmelt_iso_BX_abundance %>% filter(compartment %in% "root") %>% dplyr::select(-rep) %>% group_by(OTU, Strain, location, background, compartment) %>% dplyr::summarize(Abundance_mean_Strain = mean(WT))
#
# all_phy_psmelt_iso_BX_abundance_cum <- all_phy_psmelt_iso_BX_abundance_cum %>% group_by(Strain, location, background, compartment) %>% dplyr::summarize(Abundance_cum_Strain = sum(Abundance_mean_Strain))
#
# all_phy_psmelt_iso_BX_abundance_cum %>%
# ggplot(aes(x = Strain, y = Abundance_cum_Strain, group = location)) +
# geom_bar(aes(fill = location), stat = "identity") +
# facet_wrap(~location) +
# theme_bw()+
# theme(axis.text.x=element_text(angle = 90, hjust = 0, vjust = 0.5 ))
#
#
# all_phy_psmelt_iso_BX_abundance_cum %>%
# filter(location %in% "Changins") %>%
# ggplot(aes(x = Strain, y = Abundance_cum_Strain, group = location)) +
# geom_bar(aes(fill = location), stat = "identity") +
# facet_wrap(~location) +
# theme_bw()+
# theme(axis.text.x=element_text(angle = 90, hjust = 0, vjust = 0.5 ))
#
# write_rds(all_phy_psmelt_iso_BX_abundance_cum, "all_phy_psmelt_iso_BX_abundance_cum.rds")# all_phy_psmelt_iso_BX_abundance <- read_rds("all_phy_psmelt_iso_BX_abundance.rds")strains <- c("LMZ1", "LMX92", "LMX9231", "LMC1", "LMK1", "LME3", "LAC11", "LWO15", "LPD12", "LMX9", "LPD11", "LMX4", "LMX11", "LMY1", "LWO6", "LPB4.O", "LPD21", "LPD2", "LST26", "LPD22", "LPD32", "LPD121", "LPD34", "LPD33", "LMS1", "LMU1", "LST72", "LST61", "LST521", "LST82", "LST21", "LST22", "LST28", "LST18", "LST23", "LST52", "LST24", "LST15", "LST16", "LST14", "LST25", "LST20", "LST17", "LST27", "LST60", "LST19", "LST11", "LST12", "LST13", "LRH8.O", "LRC7.O", "LRH11", "LRH12", "LRH13", "LRC7.S", "LMQ1", "LSP13", "LMC3", "LWH4", "LBH3", "LMA1", "LWS12", "LBO6", "LBO4", "LWS2", "LWH9", "LBH2", "LWH8", "LBH7", "LDE1", "LBA112", "LBA18", "LBA111", "LBA1", "LWS1", "LWS15", "LMH1", "LBA71", "LMW1", "LMJ1", "LBA3", "LWS11", "LMA2", "LMO1", "LBA20", "LBA21", "LMM1", "LMP1", "LME1", "LME2", "LMX8", "LMX1", "LPE13", "LMF1", "LMG1", "LMG2", "LMV1", "LPA21", "LMX5", "LBS1", "LMD1", "LMD2", "LAR12", "LPA2", "LWH5", "LAR21", "LML1", "LWH1", "LWO8", "LWH3", "LBO1", "LWH7", "LWO2", "LMI12", "LMI21", "LWS13", "LMI1", "LMX2", "LMX6", "LMI22", "LMI18", "LWH10", "LMI14", "LMX7", "LMB2", "LMI11", "LMI1x", "LMI2x", "LWO5", "LWH12", "LWO13", "LWH13", "LWO12", "LMI51", "LBO3", "LMX3", "LMI15", "LMI13", "LMI111", "LMI112", "LMI81", "LMI32", "LMI62", "LMI522", "LMI17", "LMI121", "LWH11", "LWO14", "LBO11", "LMT1", "LMN1")# scales::show_col(calc_pal()(12))
# all_phy_psmelt_iso_BX_abundance %<>% na.omit()
#
# all_phy_psmelt_iso_BX_abundance$cols_family <- as.character(all_phy_psmelt_iso_BX_abundance$family)
#
# all_phy_psmelt_iso_BX_abundance[all_phy_psmelt_iso_BX_abundance$family=="Bacillaceae" , ]$cols_family <- "#004586"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Chitinophagaceae" , ]$cols_family <- "#ff420e"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Enterobacteriaceae" , ]$cols_family <- "#ffd320"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Erwiniaceae" , ]$cols_family <- "#579d1c"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Microbacteriaceae" , ]$cols_family <- "#7e0021"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Micrococcaceae" , ]$cols_family <- "#83caff"
# #all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Nocardioidaceae" , ]$cols_family <- "#314004"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Oxalobacteraceae" , ]$cols_family <- "#aecf00"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Burkholderiaceae" , ]$cols_family <- "#aecf00"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Pseudomonadaceae" , ]$cols_family <- "#4b1f6f"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Rhizobiaceae", ]$cols_family <- "#ff950e"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Sphingomonadaceae", ]$cols_family <- "#c5000b"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Xanthomonadaceae", ]$cols_family <- "#0084d1"
#
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Streptomycetaceae" , ]$cols_family <- "#8b995a"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Flavobacteriaceae" , ]$cols_family <- "#F0D5B4"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Paenibacillaceae" , ]$cols_family <- "#8f9ec9"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Planococcaceae", ]$cols_family <- "#7F5757"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Chitinophagaceae", ]$cols_family <- "#6D4600"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Moraxellaceae", ]$cols_family <- "#a73e62"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Sphingobacteriaceae", ]$cols_family <- "#c75536"
# all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family=="Deinococcaceae", ]$cols_family <- "#031e33"
#
# # all_phy_psmelt_iso_BX_abundance[ all_phy_psmelt_iso_BX_abundance$family==NA, ]$cols_family <- "dimgrey"
# # table(all_phy_psmelt_iso_BX_abundance$cols_family)
#
# ## collapsed color vector for each level
# temp <- data.frame(all_phy_psmelt_iso_BX_abundance$family, all_phy_psmelt_iso_BX_abundance$cols_family)
# temp <- plyr::ddply(temp, .variables="all_phy_psmelt_iso_BX_abundance.cols_family", .fun=unique) #library(plyr)
# all_phy_psmelt_iso_BX_abundance_level_cols_family <- as.character(temp[,2])
# names(all_phy_psmelt_iso_BX_abundance_level_cols_family) <- temp[,1]Some strains do not match an ASV or the ASV has in one of the genotypes and abundance = 0, these families are excluded in this plot: - Chitinophagaceae - Deinococcaceae - Moraxellaceae - Nocardioidaceae - Sphingobacteriaceae
Fig. 2A BX Tolerance: BX dependent colonization 630 x 600
# all_phy_psmelt_iso_BX_abundance %>%
# filter(Strain %in% strains) %>%
# filter(compartment %in% c("rhizo", "root")) %>%
# filter(location %in% "Changins") %>%
# # mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# # mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
# filter(!log2FC %in% c(-Inf, Inf, NA, NaN)) %>%
# # filter(!log2FC %in% c(NA, NaN)) %>%
# mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
# mutate(OTU = reorder(OTU, desc(family))) %>%
# # ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
# ggplot(aes(y = log2FC, x = OTU)) +
# geom_point(aes(color=family, shape = compartment), size = 3, stat = "summary", show.legend = TRUE) +
# geom_hline(yintercept = 0) +
# coord_flip() +
# theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +
# scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_level_cols_family) +
# labs(x = "",
# y = "log2 fold change WT-bx1",
# shape = "compartment")# all_phy_psmelt_iso_BX_abundance %>%
# filter(Strain %in% strains) %>%
# filter(compartment %in% c("rhizo", "root")) %>%
# filter(location %in% "Changins") %>%
# # mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# # mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
# filter(!WTbx1dif_zscore %in% c(-Inf, Inf, NA, NaN)) %>%
# # filter(!log2FC %in% c(NA, NaN)) %>%
# mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
# mutate(OTU = reorder(OTU, desc(family))) %>%
# # ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
# ggplot(aes(y = WTbx1dif_zscore , x = OTU)) +
# geom_point(aes(color=family, shape = compartment), size = 3, stat = "summary", show.legend = TRUE) +
# geom_hline(yintercept = 0) +
# coord_flip() +
# theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +
# scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_level_cols_family) +
# labs(x = "",
# y = "zscore WT-bx1",
# shape = "compartment")# scales::show_col(calc_pal()(12))
# all_phy_psmelt_iso_BX_abundance_meanOTU %<>% na.omit()
all_phy_psmelt_iso_BX_abundance_meanOTU$cols_family <- as.character(all_phy_psmelt_iso_BX_abundance_meanOTU$family)
all_phy_psmelt_iso_BX_abundance_meanOTU[all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Bacillaceae" , ]$cols_family <- "#004586"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Chitinophagaceae" , ]$cols_family <- "#ff420e"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Enterobacteriaceae" , ]$cols_family <- "#ffd320"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Erwiniaceae" , ]$cols_family <- "#579d1c"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Microbacteriaceae" , ]$cols_family <- "#7e0021"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Micrococcaceae" , ]$cols_family <- "#83caff"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Nocardioidaceae" , ]$cols_family <- "#314004"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Oxalobacteraceae" , ]$cols_family <- "#aecf00"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Burkholderiaceae" , ]$cols_family <- "#aecf00"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Pseudomonadaceae" , ]$cols_family <- "#4b1f6f"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Rhizobiaceae", ]$cols_family <- "#ff950e"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Sphingomonadaceae", ]$cols_family <- "#c5000b"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Xanthomonadaceae", ]$cols_family <- "#0084d1"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Streptomycetaceae" , ]$cols_family <- "#8b995a"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Flavobacteriaceae" , ]$cols_family <- "#F0D5B4"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Paenibacillaceae" , ]$cols_family <- "#8f9ec9"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Planococcaceae", ]$cols_family <- "#7F5757"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Chitinophagaceae", ]$cols_family <- "#6D4600"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Moraxellaceae", ]$cols_family <- "#a73e62"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Sphingobacteriaceae", ]$cols_family <- "#c75536"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Deinococcaceae", ]$cols_family <- "#031e33"
all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family=="Weeksellaceae" , ]$cols_family <- "black"
# all_phy_psmelt_iso_BX_abundance_meanOTU[ all_phy_psmelt_iso_BX_abundance_meanOTU$family==NA, ]$cols_family <- "dimgrey"
# table(all_phy_psmelt_iso_BX_abundance_meanOTU$cols_family)
## collapsed color vector for each level
temp <- data.frame(all_phy_psmelt_iso_BX_abundance_meanOTU$family, all_phy_psmelt_iso_BX_abundance_meanOTU$cols_family)
temp <- plyr::ddply(temp, .variables="all_phy_psmelt_iso_BX_abundance_meanOTU.cols_family", .fun=unique) #library(plyr)
all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family <- as.character(temp[,2])
names(all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) <- temp[,1]# all_phy_psmelt_iso_BX_abundance_meanOTU_meanOTU$family <- gsub("Burkholderiaceae", "Oxalobacteraceae", all_phy_psmelt_iso_BX_abundance_meanOTU$family)
ASV_WTbx1dif <- all_phy_psmelt_iso_BX_abundance_meanOTU %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
filter(!WTbx1dif_mean %in% 0) %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = WTbx1dif_mean, x = reorder(OTU, desc(family)))) +
geom_point(aes(color=family, shape = compartment), size = 3, stat = "summary", show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
scale_shape_manual(values=c(15, 16, 17, 18)) +
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WTbx1dif_mean",
shape = "compartment")
ASV_WTbx1dif
# library(Cairo)
#
# Cairo(file="ASV_WTbx1dif.png",
# type="png",
# units="in",
# height = 20,
# width = 10,
# pointsize = 1,
# dpi=300)
# ASV_WTbx1dif
# dev.off()# all_phy_psmelt_iso_BX_abundance_meanOTU_meanOTU$family <- gsub("Burkholderiaceae", "Oxalobacteraceae", all_phy_psmelt_iso_BX_abundance_meanOTU$family)
ASV_WTbx1dif_OTU <- all_phy_psmelt_iso_BX_abundance_meanOTU %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
filter(!WTbx1dif_mean %in% 0) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = WTbx1dif_mean, x = family)) +
geom_boxplot(aes(color = family)) +
geom_jitter(aes(color=family), show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ compartment) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
ASV_WTbx1dif_OTU
library(Cairo)
#
# Cairo(file="ASV_WTbx1dif_OTU.png",
# type="png",
# units="in",
# height = 20,
# width = 10,
# pointsize = 1,
# dpi=300)
# ASV_WTbx1dif_OTU
# dev.off()Select only well represented ASVs
- only select ASVs which are found in min. 3 samples
count_sample_ASV <- all_phy_psmelt_iso_BX %>% filter(!Abundance %in% 0) %>% dplyr::select(OTU, rep, background, compartment, genotype, location, family) %>% group_by(OTU, background, compartment, genotype, location, family) %>% unique() %>% count()
count_sample_ASV %>% filter(OTU %in% "ASV2230")## # A tibble: 3 × 7
## # Groups: OTU, background, compartment, genotype, location, family [3]
## OTU background compartment genotype location family n
## <chr> <fct> <fct> <fct> <fct> <chr> <int>
## 1 ASV2230 B73 rhizo WT Changins Streptomycetaceae 1
## 2 ASV2230 B73 root WT Changins Streptomycetaceae 2
## 3 ASV2230 B73 root bx1 Changins Streptomycetaceae 1count_sample_ASV_well_represented <- count_sample_ASV %>% filter(location %in% "Changins") %>% filter(compartment %in% "root") %>% filter(n > 2)
represented_OTU <- count_sample_ASV_well_represented$OTU %>% unique()all_phy_psmelt_iso_BX_abundance$family <- gsub("Burkholderiaceae", "Oxalobacteraceae", all_phy_psmelt_iso_BX_abundance$family)
ASV_WTbx1dif_OTU <- all_phy_psmelt_iso_BX_abundance %>% filter(OTU %in% represented_OTU) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
filter(!WTbx1dif %in% 0) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = WTbx1dif, x = interaction(family, OTU))) +
geom_boxplot(aes(color = family)) +
geom_jitter(aes(color=family), show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ compartment) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
ASV_WTbx1dif_OTU
- only select ASVs which are found in all sequenced samples
min. samples per treatment in dataset are 6 (soil, rhizo, root W22 WT Zurich and root WT W22 Ithaca), max are 12 (soil, rhizo, root bx1 W22 Zurich)
nr_of_samples_per_treatment <- all_phy_psmelt_iso_BX %>%
dplyr::select(rep, background, compartment, genotype, location) %>%
group_by(background, compartment, genotype, location) %>%
unique() %>%
count()
nr_of_samples_per_treatment$n %>% max()## [1] 12nr_of_samples_per_treatment$n %>% min()## [1] 6nr_of_samples_per_treatment %>% knitr::kable()| background | compartment | genotype | location | n |
|---|---|---|---|---|
| B73 | soil | WT | Zurich | 11 |
| B73 | soil | bx1 | Zurich | 12 |
| B73 | rhizo | WT | Changins | 10 |
| B73 | rhizo | WT | Zurich | 11 |
| B73 | rhizo | bx1 | Changins | 7 |
| B73 | rhizo | bx1 | Zurich | 12 |
| B73 | root | WT | Changins | 10 |
| B73 | root | WT | Zurich | 11 |
| B73 | root | bx1 | Changins | 7 |
| B73 | root | bx1 | Zurich | 12 |
| W22 | soil | WT | Ithaca | 8 |
| W22 | soil | WT | Zurich | 6 |
| W22 | soil | bx1 | Ithaca | 8 |
| W22 | soil | bx1 | Zurich | 11 |
| W22 | rhizo | WT | Ithaca | 8 |
| W22 | rhizo | WT | Zurich | 6 |
| W22 | rhizo | bx1 | Ithaca | 8 |
| W22 | rhizo | bx1 | Zurich | 11 |
| W22 | root | WT | Ithaca | 6 |
| W22 | root | WT | Zurich | 6 |
| W22 | root | WT | Sheffield | 8 |
| W22 | root | bx1 | Ithaca | 7 |
| W22 | root | bx1 | Zurich | 11 |
| W22 | root | bx1 | Sheffield | 8 |
count_sample_ASV <- all_phy_psmelt_iso_BX %>%
filter(!Abundance %in% 0) %>%
dplyr::select(OTU, rep, background, compartment, genotype, location, family) %>%
group_by(OTU, background, compartment, genotype, location, family) %>% unique() %>% count()
count_sample_ASV_in_all_samples <- count_sample_ASV %>% filter(location %in% "Changins") %>% filter(compartment %in% "root") %>% filter(n > 5)
ASV_in_all_samples <- count_sample_ASV_in_all_samples$OTU %>% unique()all_phy_psmelt_iso_BX_abundance$family <- gsub("Burkholderiaceae", "Oxalobacteraceae", all_phy_psmelt_iso_BX_abundance$family)
ASV_WTbx1dif_OTU <- all_phy_psmelt_iso_BX_abundance %>% filter(OTU %in% ASV_in_all_samples) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
filter(!WTbx1dif %in% 0) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = WTbx1dif, x = interaction(family, OTU))) +
geom_boxplot(aes(color = family)) +
geom_jitter(aes(color=family), show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ compartment) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
ASV_WTbx1dif_OTU
###best mapping ASVs
all_phy_psmelt_iso_BX_identity_strains <- all_phy_psmelt_iso %>%
filter(OTU %in% ASV_in_all_samples) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
filter(location %in% "Changins") %>%
dplyr::select(OTU, family, Strain, '%') %>%
dplyr::rename(identity = '%')
all_phy_psmelt_iso_BX_identity_strains_wide <- all_phy_psmelt_iso_BX_identity_strains %>%
unique() %>%
pivot_wider(names_from = OTU, values_from = identity) %>%
as.data.frame() %>%
replace(.=="NULL", NA)
# write.table(all_phy_psmelt_iso_BX_identity_strains_wide %>% as.data.frame(), "all_phy_psmelt_iso_BX_identity_strains_wide.csv")# *Bacillaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Bacillaceae") %>% unique()## # A tibble: 80 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [6]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMX1 0.989
## 2 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMX8 0.989
## 3 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA21 0.984
## 4 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMM1 0.984
## 5 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMP1 0.984
## 6 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LME1 0.976
## 7 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LME2 0.976
## 8 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA21 0.974
## 9 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMJ1 0.971
## 10 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LMX1 0.989
## # ℹ 70 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Bacillaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 20 strains ## # A tibble: 6 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [6]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1182 Firmicutes Bacillaceae Bacillus Changins B73 WT 8
## 2 ASV1182 Firmicutes Bacillaceae Bacillus Changins B73 bx1 8
## 3 ASV1322 Firmicutes Bacillaceae Bacillus Changins B73 WT 20
## 4 ASV1322 Firmicutes Bacillaceae Bacillus Changins B73 bx1 20
## 5 ASV3604 Firmicutes Bacillaceae Bacillus Changins B73 WT 10
## 6 ASV3604 Firmicutes Bacillaceae Bacillus Changins B73 bx1 10## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Bacillaceae") %>% filter(identity %in% 1.0000000)## # A tibble: 12 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA21 1
## 2 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMM1 1
## 3 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMP1 1
## 4 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA21 1
## 5 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMM1 1
## 6 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LMP1 1
## 7 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LBA21 1
## 8 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LMM1 1
## 9 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LMP1 1
## 10 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LBA21 1
## 11 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LMM1 1
## 12 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LMP1 1all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Bacillaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1322 Firmicutes Bacillaceae Bacillus Changins B73 WT 3
## 2 ASV1322 Firmicutes Bacillaceae Bacillus Changins B73 bx1 3# 3 strains mapping 100% to ASV1322
# other strains not mapping 100%
Bacillaceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Bacillaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Bacillaceae_100_id <- Bacillaceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Bacillaceae") %>% filter(!Strain %in% Bacillaceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 6 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [6]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1182 Firmicutes Bacillaceae Bacillus Changins B73 WT 5
## 2 ASV1182 Firmicutes Bacillaceae Bacillus Changins B73 bx1 5
## 3 ASV1322 Firmicutes Bacillaceae Bacillus Changins B73 WT 17
## 4 ASV1322 Firmicutes Bacillaceae Bacillus Changins B73 bx1 17
## 5 ASV3604 Firmicutes Bacillaceae Bacillus Changins B73 WT 7
## 6 ASV3604 Firmicutes Bacillaceae Bacillus Changins B73 bx1 7all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Bacillaceae") %>%
filter(!Strain %in% Bacillaceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 58 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [6]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA1 0.976
## 2 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LBA1 0.976
## 3 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA112 0.976
## 4 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LBA112 0.976
## 5 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA20 0.979
## 6 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LBA20 0.979
## 7 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA3 0.976
## 8 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LBA3 0.976
## 9 Firmicutes Bacillus Changins B73 WT ASV1… Bacil… LBA71 0.976
## 10 Firmicutes Bacillus Changins B73 bx1 ASV1… Bacil… LBA71 0.976
## # ℹ 48 more rows# OTU family Strain identity
# 1 ASV1322 Bacillaceae LBA1 0.9762533
# 2 ASV1322 Bacillaceae LBA112 0.9762533
# 3 ASV1322 Bacillaceae LBA20 0.9789474
# 4 ASV1322 Bacillaceae LBA3 0.9762533
# 5 ASV1322 Bacillaceae LBA71 0.9762533
# 6 ASV1322 Bacillaceae LMA2 0.9788918
# 9 ASV1322 Bacillaceae LME1 0.9868074
# 12 ASV1322 Bacillaceae LME2 0.9868074
# 14 ASV1322 Bacillaceae LMH1 0.9762533
# 15 ASV1182 Bacillaceae LMJ1 0.9709763 !
# 16 ASV1322 Bacillaceae LMJ1 0.9841689
# 17 ASV1322 Bacillaceae LMO1 0.9788918
# 19 ASV1322 Bacillaceae LMW1 0.9762533
# 20 ASV1182 Bacillaceae LMX1 0.9894459 !
# 23 ASV1182 Bacillaceae LMX8 0.9894459 !
# 26 ASV1322 Bacillaceae LWS1 0.9709763
# 27 ASV1322 Bacillaceae LWS11 0.9788918
# 29 ASV1322 Bacillaceae LWS15 0.9709763
# Bacillaceae: ASV1322, except LMJ1, LMX1, LMX8 ASV1182
# *Microbacteriaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Microbacteriaceae") %>% unique()## # A tibble: 160 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI62 1
## 2 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI11 1
## 3 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI13 1
## 4 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI14 1
## 5 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI15 1
## 6 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI18 1
## 7 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI51 1
## 8 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMB2 1
## 9 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI1x 1
## 10 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI2x 1
## # ℹ 150 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Microbacteriaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 42 strains ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1078 Actinobacteria Microbacteria… Micr… Changins B73 WT 42
## 2 ASV1078 Actinobacteria Microbacteria… Micr… Changins B73 bx1 42
## 3 ASV968 Actinobacteria Microbacteria… Micr… Changins B73 WT 32
## 4 ASV968 Actinobacteria Microbacteria… Micr… Changins B73 bx1 32## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Microbacteriaceae") %>% filter(identity %in% 1.0000000)## # A tibble: 128 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI62 1
## 2 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI11 1
## 3 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI13 1
## 4 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI14 1
## 5 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI15 1
## 6 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI18 1
## 7 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI51 1
## 8 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMB2 1
## 9 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI1x 1
## 10 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI2x 1
## # ℹ 118 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Microbacteriaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1078 Actinobacteria Microbacteria… Micr… Changins B73 WT 23
## 2 ASV1078 Actinobacteria Microbacteria… Micr… Changins B73 bx1 23
## 3 ASV968 Actinobacteria Microbacteria… Micr… Changins B73 WT 9
## 4 ASV968 Actinobacteria Microbacteria… Micr… Changins B73 bx1 9# 32 strains mapping 100% to ASV1078
# other strains not mapping 100%
micro_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Microbacteriaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
micro_100_id <- micro_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Microbacteriaceae") %>% filter(!Strain %in% micro_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1078 Actinobacteria Microbacteria… Micr… Changins B73 WT 10
## 2 ASV1078 Actinobacteria Microbacteria… Micr… Changins B73 bx1 10all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Microbacteriaceae") %>% filter(!Strain %in% micro_100_id) %>% unique()## # A tibble: 20 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI111 0.997
## 2 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI112 0.997
## 3 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI121 0.997
## 4 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI17 0.997
## 5 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI22 0.997
## 6 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI32 0.997
## 7 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI522 0.997
## 8 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI81 0.997
## 9 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LMI1 0.984
## 10 Actinobacter… Micr… Changins B73 WT ASV1… Micro… LBO11 0.979
## 11 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI111 0.997
## 12 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI112 0.997
## 13 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI121 0.997
## 14 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI17 0.997
## 15 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI22 0.997
## 16 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI32 0.997
## 17 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI522 0.997
## 18 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI81 0.997
## 19 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LMI1 0.984
## 20 Actinobacter… Micr… Changins B73 bx1 ASV1… Micro… LBO11 0.979# 10 strains mapping to ASV1078 (0.9973615, 0.9841689, 0.9788918)
# Microbacteriaceae: ASV1078
# *Micrococcaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Micrococcaceae") %>% unique()## # A tibble: 24 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA2 0.997
## 2 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA21 0.997
## 3 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LAR21 0.995
## 4 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA2 0.995
## 5 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA21 0.995
## 6 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LWH5 0.987
## 7 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LMD1 0.982
## 8 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LMD2 0.982
## 9 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LBS1 0.982
## 10 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LMX5 0.979
## # ℹ 14 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Micrococcaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 9 strains ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV105 Actinobacteria Micrococcaceae Pseud… Changins B73 WT 8
## 2 ASV105 Actinobacteria Micrococcaceae Pseud… Changins B73 bx1 8
## 3 ASV972 Actinobacteria Micrococcaceae Arthr… Changins B73 WT 1
## 4 ASV972 Actinobacteria Micrococcaceae Arthr… Changins B73 bx1 1## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Micrococcaceae") %>% filter(identity %in% 1.0000000)## # A tibble: 4 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacteria Arth… Changins B73 WT ASV9… Micro… LAR12 1
## 2 Actinobacteria Arth… Changins B73 WT ASV9… Micro… LAR12 1
## 3 Actinobacteria Arth… Changins B73 bx1 ASV9… Micro… LAR12 1
## 4 Actinobacteria Arth… Changins B73 bx1 ASV9… Micro… LAR12 1all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Micrococcaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV972 Actinobacteria Micrococcaceae Arthr… Changins B73 WT 1
## 2 ASV972 Actinobacteria Micrococcaceae Arthr… Changins B73 bx1 1# 1 strains mapping 100% to ASV972 (LAR12)
# other strains not mapping 100%
Micrococcaceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Micrococcaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Micrococcaceae_100_id <- Micrococcaceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Micrococcaceae") %>% filter(!Strain %in% Micrococcaceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV105 Actinobacteria Micrococcaceae Pseud… Changins B73 WT 8
## 2 ASV105 Actinobacteria Micrococcaceae Pseud… Changins B73 bx1 8all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Micrococcaceae") %>%
filter(!Strain %in% Micrococcaceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 20 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LAR21 0.995
## 2 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LAR21 0.995
## 3 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LBS1 0.982
## 4 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LBS1 0.982
## 5 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LMD1 0.982
## 6 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LMD1 0.982
## 7 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LMD2 0.982
## 8 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LMD2 0.982
## 9 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LMX5 0.979
## 10 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LMX5 0.979
## 11 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA2 0.997
## 12 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA2 0.995
## 13 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LPA2 0.997
## 14 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LPA2 0.995
## 15 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA21 0.997
## 16 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LPA21 0.995
## 17 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LPA21 0.997
## 18 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LPA21 0.995
## 19 Actinobacter… Pseu… Changins B73 WT ASV1… Micro… LWH5 0.987
## 20 Actinobacter… Pseu… Changins B73 bx1 ASV1… Micro… LWH5 0.987# 9 strains mapping to ASV105
# *Oxalobacteraceae*
all_phy_psmelt_iso_BX_identity_strains$family <- gsub("Burkholderiaceae", "Oxalobacteraceae", all_phy_psmelt_iso_BX_identity_strains$family)
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Oxalobacteraceae") %>% unique()## # A tibble: 24 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [14]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Jant… Changins B73 WT ASV1… Oxalo… LMS1 0.995
## 2 Proteobacter… Jant… Changins B73 WT ASV1… Oxalo… LMU1 0.981
## 3 Proteobacter… Jant… Changins B73 bx1 ASV1… Oxalo… LMS1 0.995
## 4 Proteobacter… Jant… Changins B73 bx1 ASV1… Oxalo… LMU1 0.981
## 5 Proteobacter… Pseu… Changins B73 WT ASV2… Oxalo… LMS1 0.970
## 6 Proteobacter… Pseu… Changins B73 bx1 ASV2… Oxalo… LMS1 0.970
## 7 Proteobacter… Duga… Changins B73 WT ASV2… Oxalo… LMU1 0.995
## 8 Proteobacter… Duga… Changins B73 WT ASV2… Oxalo… LMS1 0.976
## 9 Proteobacter… Duga… Changins B73 bx1 ASV2… Oxalo… LMU1 0.995
## 10 Proteobacter… Duga… Changins B73 bx1 ASV2… Oxalo… LMS1 0.976
## # ℹ 14 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Oxalobacteraceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 2 strains ## # A tibble: 14 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [14]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV107 Proteobacteria Oxalobacterac… Jant… Changins B73 WT 2
## 2 ASV107 Proteobacteria Oxalobacterac… Jant… Changins B73 bx1 2
## 3 ASV247 Proteobacteria Oxalobacterac… Pseu… Changins B73 WT 1
## 4 ASV247 Proteobacteria Oxalobacterac… Pseu… Changins B73 bx1 1
## 5 ASV267 Proteobacteria Oxalobacterac… Duga… Changins B73 WT 2
## 6 ASV267 Proteobacteria Oxalobacterac… Duga… Changins B73 bx1 2
## 7 ASV356 Proteobacteria Oxalobacterac… <NA> Changins B73 WT 2
## 8 ASV356 Proteobacteria Oxalobacterac… <NA> Changins B73 bx1 2
## 9 ASV452 Proteobacteria Oxalobacterac… Pseu… Changins B73 WT 2
## 10 ASV452 Proteobacteria Oxalobacterac… Pseu… Changins B73 bx1 2
## 11 ASV54 Proteobacteria Oxalobacterac… Pseu… Changins B73 WT 1
## 12 ASV54 Proteobacteria Oxalobacterac… Pseu… Changins B73 bx1 1
## 13 ASV917 Proteobacteria Oxalobacterac… Duga… Changins B73 WT 2
## 14 ASV917 Proteobacteria Oxalobacterac… Duga… Changins B73 bx1 2## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Oxalobacteraceae") %>% filter(identity %in% 1.0000000)## # A tibble: 0 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [0]
## # ℹ 9 variables: phylum <chr>, genus <chr>, location <fct>, background <fct>,
## # genotype <fct>, OTU <chr>, family <chr>, Strain <chr>, identity <dbl>all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Oxalobacteraceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 0 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [0]
## # ℹ 8 variables: OTU <chr>, phylum <chr>, family <chr>, genus <chr>,
## # location <fct>, background <fct>, genotype <fct>, n <int># 0 strains mapping 100%
# other strains not mapping 100%
Oxalobacteraceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Oxalobacteraceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Oxalobacteraceae_100_id <- Oxalobacteraceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Oxalobacteraceae") %>% filter(!Strain %in% Oxalobacteraceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 14 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [14]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV107 Proteobacteria Oxalobacterac… Jant… Changins B73 WT 2
## 2 ASV107 Proteobacteria Oxalobacterac… Jant… Changins B73 bx1 2
## 3 ASV247 Proteobacteria Oxalobacterac… Pseu… Changins B73 WT 1
## 4 ASV247 Proteobacteria Oxalobacterac… Pseu… Changins B73 bx1 1
## 5 ASV267 Proteobacteria Oxalobacterac… Duga… Changins B73 WT 2
## 6 ASV267 Proteobacteria Oxalobacterac… Duga… Changins B73 bx1 2
## 7 ASV356 Proteobacteria Oxalobacterac… <NA> Changins B73 WT 2
## 8 ASV356 Proteobacteria Oxalobacterac… <NA> Changins B73 bx1 2
## 9 ASV452 Proteobacteria Oxalobacterac… Pseu… Changins B73 WT 2
## 10 ASV452 Proteobacteria Oxalobacterac… Pseu… Changins B73 bx1 2
## 11 ASV54 Proteobacteria Oxalobacterac… Pseu… Changins B73 WT 1
## 12 ASV54 Proteobacteria Oxalobacterac… Pseu… Changins B73 bx1 1
## 13 ASV917 Proteobacteria Oxalobacterac… Duga… Changins B73 WT 2
## 14 ASV917 Proteobacteria Oxalobacterac… Duga… Changins B73 bx1 2all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Oxalobacteraceae") %>%
filter(!Strain %in% Oxalobacteraceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 24 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [14]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Jant… Changins B73 WT ASV1… Oxalo… LMS1 0.995
## 2 Proteobacter… Jant… Changins B73 bx1 ASV1… Oxalo… LMS1 0.995
## 3 Proteobacter… Pseu… Changins B73 WT ASV2… Oxalo… LMS1 0.970
## 4 Proteobacter… Pseu… Changins B73 bx1 ASV2… Oxalo… LMS1 0.970
## 5 Proteobacter… Duga… Changins B73 WT ASV2… Oxalo… LMS1 0.976
## 6 Proteobacter… Duga… Changins B73 bx1 ASV2… Oxalo… LMS1 0.976
## 7 Proteobacter… <NA> Changins B73 WT ASV3… Oxalo… LMS1 0.981
## 8 Proteobacter… <NA> Changins B73 bx1 ASV3… Oxalo… LMS1 0.981
## 9 Proteobacter… Pseu… Changins B73 WT ASV4… Oxalo… LMS1 0.970
## 10 Proteobacter… Pseu… Changins B73 bx1 ASV4… Oxalo… LMS1 0.970
## # ℹ 14 more rows# ASV267 Oxalobacteraceae LMU1 0.9946237
# ASV107 Oxalobacteraceae LMS1 0.9946237
# *Pseudomonadaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Pseudomonadaceae") %>% unique()## # A tibble: 46 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LMY1 0.997
## 2 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LPD11 0.992
## 3 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LPD12 0.992
## 4 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LMX11 0.992
## 5 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LMX4 0.992
## 6 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LMX9 0.992
## 7 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LWO6 0.992
## 8 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LWO15 0.992
## 9 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LPD12 0.981
## 10 Proteobacter… Pseu… Changins B73 bx1 ASV3… Pseud… LMY1 0.997
## # ℹ 36 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Pseudomonadaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 2 strains ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV340 Proteobacteria Pseudomonadace… Pseu… Changins B73 WT 8
## 2 ASV340 Proteobacteria Pseudomonadace… Pseu… Changins B73 bx1 8
## 3 ASV4 Proteobacteria Pseudomonadace… Pseu… Changins B73 WT 13
## 4 ASV4 Proteobacteria Pseudomonadace… Pseu… Changins B73 bx1 13## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Pseudomonadaceae") %>% filter(identity %in% 1.0000000) %>% unique()## # A tibble: 10 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LPD11 1
## 2 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LPD12 1
## 3 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LMX4 1
## 4 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LMX9 1
## 5 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LWO15 1
## 6 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LPD11 1
## 7 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LPD12 1
## 8 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LMX4 1
## 9 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LMX9 1
## 10 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LWO15 1all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Pseudomonadaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV4 Proteobacteria Pseudomonadaceae Pseu… Changins B73 WT 5
## 2 ASV4 Proteobacteria Pseudomonadaceae Pseu… Changins B73 bx1 5# 5 strains mapping 100% to ASV4
# other strains not mapping 100%
Pseudomonadaceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Pseudomonadaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Pseudomonadaceae_100_id <- Pseudomonadaceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Pseudomonadaceae") %>% filter(!Strain %in% Pseudomonadaceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV340 Proteobacteria Pseudomonadace… Pseu… Changins B73 WT 3
## 2 ASV340 Proteobacteria Pseudomonadace… Pseu… Changins B73 bx1 3
## 3 ASV4 Proteobacteria Pseudomonadace… Pseu… Changins B73 WT 8
## 4 ASV4 Proteobacteria Pseudomonadace… Pseu… Changins B73 bx1 8all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Pseudomonadaceae") %>%
filter(!Strain %in% Pseudomonadaceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 22 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LMX11 0.992
## 2 Proteobacter… Pseu… Changins B73 bx1 ASV3… Pseud… LMX11 0.992
## 3 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LMX11 0.997
## 4 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LMX11 0.997
## 5 Proteobacter… Pseu… Changins B73 WT ASV3… Pseud… LMY1 0.997
## 6 Proteobacter… Pseu… Changins B73 bx1 ASV3… Pseud… LMY1 0.997
## 7 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LMY1 0.992
## 8 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LMY1 0.992
## 9 Proteobacter… Pseu… Changins B73 WT ASV4 Pseud… LPB4.O 0.974
## 10 Proteobacter… Pseu… Changins B73 bx1 ASV4 Pseud… LPB4.O 0.974
## # ℹ 12 more rows# 7 strains mapping to ASV4, one strain mapping to ASV340
# *Rhizobiaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Rhizobiaceae") %>% unique()## # A tibble: 14 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Neor… Changins B73 WT ASV1… Rhizo… LMQ1 0.992
## 2 Proteobacter… Neor… Changins B73 bx1 ASV1… Rhizo… LMQ1 0.992
## 3 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRH12 1
## 4 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRH13 1
## 5 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRH11 1
## 6 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRC7.O 1
## 7 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRC7.S 1
## 8 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRH11 0.997
## 9 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRH12 1
## 10 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRH13 1
## 11 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRH11 1
## 12 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRC7.O 1
## 13 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRC7.S 1
## 14 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRH11 0.997all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Rhizobiaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 6 strains ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1000 Proteobacteria Rhizobiaceae Neorhi… Changins B73 WT 1
## 2 ASV1000 Proteobacteria Rhizobiaceae Neorhi… Changins B73 bx1 1
## 3 ASV8 Proteobacteria Rhizobiaceae Allorh… Changins B73 WT 5
## 4 ASV8 Proteobacteria Rhizobiaceae Allorh… Changins B73 bx1 5## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Rhizobiaceae") %>% filter(identity %in% 1.0000000) %>% unique()## # A tibble: 10 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRH12 1
## 2 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRH13 1
## 3 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRH11 1
## 4 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRC7.O 1
## 5 Proteobacter… Allo… Changins B73 WT ASV8 Rhizo… LRC7.S 1
## 6 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRH12 1
## 7 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRH13 1
## 8 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRH11 1
## 9 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRC7.O 1
## 10 Proteobacter… Allo… Changins B73 bx1 ASV8 Rhizo… LRC7.S 1all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Rhizobiaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV8 Proteobacteria Rhizobiaceae Allorhiz… Changins B73 WT 5
## 2 ASV8 Proteobacteria Rhizobiaceae Allorhiz… Changins B73 bx1 5# 5 strains mapping 100% to ASV8
# other strains not mapping 100%
Rhizobiaceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Rhizobiaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Rhizobiaceae_100_id <- Rhizobiaceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Rhizobiaceae") %>% filter(!Strain %in% Rhizobiaceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV1000 Proteobacteria Rhizobiaceae Neorhi… Changins B73 WT 1
## 2 ASV1000 Proteobacteria Rhizobiaceae Neorhi… Changins B73 bx1 1all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Rhizobiaceae") %>%
filter(!Strain %in% Rhizobiaceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 2 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacteria Neor… Changins B73 WT ASV1… Rhizo… LMQ1 0.992
## 2 Proteobacteria Neor… Changins B73 bx1 ASV1… Rhizo… LMQ1 0.992# 1 strains mapping to ASV4, one strain mapping to ASV1000
# *Sphingomonadaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Sphingomonadaceae") %>% unique()## # A tibble: 28 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LSP13 1
## 2 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LMA1 1
## 3 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LMC3 1
## 4 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH2 1
## 5 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH3 1
## 6 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH7 1
## 7 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBO4 1
## 8 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBO6 1
## 9 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LWH4 1
## 10 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LWH8 1
## # ℹ 18 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Sphingomonadaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 13 strains ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV3 Proteobacteria Sphingomonadac… Sphi… Changins B73 WT 13
## 2 ASV3 Proteobacteria Sphingomonadac… Sphi… Changins B73 bx1 13
## 3 ASV784 Proteobacteria Sphingomonadac… Sphi… Changins B73 WT 1
## 4 ASV784 Proteobacteria Sphingomonadac… Sphi… Changins B73 bx1 1## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Sphingomonadaceae") %>% filter(identity %in% 1.0000000) %>% unique()## # A tibble: 24 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LSP13 1
## 2 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LMA1 1
## 3 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LMC3 1
## 4 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH2 1
## 5 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH3 1
## 6 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH7 1
## 7 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBO4 1
## 8 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBO6 1
## 9 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LWH4 1
## 10 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LWH8 1
## # ℹ 14 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Sphingomonadaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV3 Proteobacteria Sphingomonadace… Sphi… Changins B73 WT 12
## 2 ASV3 Proteobacteria Sphingomonadace… Sphi… Changins B73 bx1 12# 12 strains mapping 100% to ASV3
# other strains not mapping 100%
Sphingomonadaceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Sphingomonadaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Sphingomonadaceae_100_id <- Sphingomonadaceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Sphingomonadaceae") %>% filter(!Strain %in% Sphingomonadaceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 4 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV3 Proteobacteria Sphingomonadac… Sphi… Changins B73 WT 1
## 2 ASV3 Proteobacteria Sphingomonadac… Sphi… Changins B73 bx1 1
## 3 ASV784 Proteobacteria Sphingomonadac… Sphi… Changins B73 WT 1
## 4 ASV784 Proteobacteria Sphingomonadac… Sphi… Changins B73 bx1 1all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Sphingomonadaceae") %>%
filter(!Strain %in% Rhizobiaceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 28 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [4]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH2 1
## 2 Proteobacter… Sphi… Changins B73 bx1 ASV3 Sphin… LBH2 1
## 3 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH3 1
## 4 Proteobacter… Sphi… Changins B73 bx1 ASV3 Sphin… LBH3 1
## 5 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBH7 1
## 6 Proteobacter… Sphi… Changins B73 bx1 ASV3 Sphin… LBH7 1
## 7 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBO4 1
## 8 Proteobacter… Sphi… Changins B73 bx1 ASV3 Sphin… LBO4 1
## 9 Proteobacter… Sphi… Changins B73 WT ASV3 Sphin… LBO6 1
## 10 Proteobacter… Sphi… Changins B73 bx1 ASV3 Sphin… LBO6 1
## # ℹ 18 more rows# 1 strains mapping to ASV3
# *Streptomycetaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Streptomycetaceae") %>% unique()## # A tibble: 40 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [18]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMG1 0.984
## 2 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMG2 0.984
## 3 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMF1 0.971
## 4 Actinobacter… Stre… Changins B73 bx1 ASV1… Strep… LMG1 0.984
## 5 Actinobacter… Stre… Changins B73 bx1 ASV1… Strep… LMG2 0.984
## 6 Actinobacter… Stre… Changins B73 bx1 ASV1… Strep… LMF1 0.971
## 7 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMG1 0.979
## 8 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMG2 0.979
## 9 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMF1 0.977
## 10 Actinobacter… Stre… Changins B73 bx1 ASV1… Strep… LMG1 0.979
## # ℹ 30 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Streptomycetaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 3 strains ## # A tibble: 18 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [18]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV100 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 2 ASV100 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 3 ASV1317 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 4 ASV1317 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 5 ASV1521 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 6 ASV1521 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 7 ASV2397 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 8 ASV2397 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 9 ASV265 Actinobacteria Streptomycet… Stre… Changins B73 WT 1
## 10 ASV265 Actinobacteria Streptomycet… Stre… Changins B73 bx1 1
## 11 ASV382 Actinobacteria Streptomycet… Stre… Changins B73 WT 2
## 12 ASV382 Actinobacteria Streptomycet… Stre… Changins B73 bx1 2
## 13 ASV49 Actinobacteria Streptomycet… Stre… Changins B73 WT 2
## 14 ASV49 Actinobacteria Streptomycet… Stre… Changins B73 bx1 2
## 15 ASV538 Actinobacteria Streptomycet… Stre… Changins B73 WT 1
## 16 ASV538 Actinobacteria Streptomycet… Stre… Changins B73 bx1 1
## 17 ASV64 Actinobacteria Streptomycet… Stre… Changins B73 WT 2
## 18 ASV64 Actinobacteria Streptomycet… Stre… Changins B73 bx1 2## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Streptomycetaceae") %>% filter(identity %in% 1.0000000) %>% unique()## # A tibble: 0 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [0]
## # ℹ 9 variables: phylum <chr>, genus <chr>, location <fct>, background <fct>,
## # genotype <fct>, OTU <chr>, family <chr>, Strain <chr>, identity <dbl>all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Streptomycetaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 0 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [0]
## # ℹ 8 variables: OTU <chr>, phylum <chr>, family <chr>, genus <chr>,
## # location <fct>, background <fct>, genotype <fct>, n <int># 0 strains mapping 100%
# other strains not mapping 100%
Streptomycetaceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Streptomycetaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Streptomycetaceae_100_id <- Streptomycetaceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Streptomycetaceae") %>% filter(!Strain %in% Streptomycetaceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 18 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [18]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV100 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 2 ASV100 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 3 ASV1317 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 4 ASV1317 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 5 ASV1521 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 6 ASV1521 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 7 ASV2397 Actinobacteria Streptomycet… Stre… Changins B73 WT 3
## 8 ASV2397 Actinobacteria Streptomycet… Stre… Changins B73 bx1 3
## 9 ASV265 Actinobacteria Streptomycet… Stre… Changins B73 WT 1
## 10 ASV265 Actinobacteria Streptomycet… Stre… Changins B73 bx1 1
## 11 ASV382 Actinobacteria Streptomycet… Stre… Changins B73 WT 2
## 12 ASV382 Actinobacteria Streptomycet… Stre… Changins B73 bx1 2
## 13 ASV49 Actinobacteria Streptomycet… Stre… Changins B73 WT 2
## 14 ASV49 Actinobacteria Streptomycet… Stre… Changins B73 bx1 2
## 15 ASV538 Actinobacteria Streptomycet… Stre… Changins B73 WT 1
## 16 ASV538 Actinobacteria Streptomycet… Stre… Changins B73 bx1 1
## 17 ASV64 Actinobacteria Streptomycet… Stre… Changins B73 WT 2
## 18 ASV64 Actinobacteria Streptomycet… Stre… Changins B73 bx1 2all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Streptomycetaceae") %>%
filter(!Strain %in% Streptomycetaceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 40 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [18]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMF1 0.971
## 2 Actinobacter… Stre… Changins B73 bx1 ASV1… Strep… LMF1 0.971
## 3 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMF1 0.977
## 4 Actinobacter… Stre… Changins B73 bx1 ASV1… Strep… LMF1 0.977
## 5 Actinobacter… Stre… Changins B73 WT ASV1… Strep… LMF1 0.971
## 6 Actinobacter… Stre… Changins B73 bx1 ASV1… Strep… LMF1 0.971
## 7 Actinobacter… Stre… Changins B73 WT ASV2… Strep… LMF1 0.974
## 8 Actinobacter… Stre… Changins B73 bx1 ASV2… Strep… LMF1 0.974
## 9 Actinobacter… Stre… Changins B73 WT ASV49 Strep… LMF1 0.971
## 10 Actinobacter… Stre… Changins B73 bx1 ASV49 Strep… LMF1 0.971
## # ℹ 30 more rows# OTU family Strain identity
# 5 ASV538 Streptomycetaceae LMF1 0.9844156
# 12 ASV1521 Streptomycetaceae LMG1 0.9844156
# 20 ASV1521 Streptomycetaceae LMG2 0.9844156
# 1 strains mapping to ASV538, one strain mapping to ASV1521
# *Xanthomonadaceae*
## total strains
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Xanthomonadaceae") %>% unique()## # A tibble: 68 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST23 1
## 2 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST12 1
## 3 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST15 1
## 4 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST11 1
## 5 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST13 1
## 6 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST14 1
## 7 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST16 1
## 8 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST17 1
## 9 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST19 1
## 10 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST20 1
## # ℹ 58 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Xanthomonadaceae") %>% dplyr::select(Strain) %>% unique() %>% count() # 23 strains ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV12 Proteobacteria Xanthomonadaceae Sten… Changins B73 WT 23
## 2 ASV12 Proteobacteria Xanthomonadaceae Sten… Changins B73 bx1 23## strains mapping 100%
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Xanthomonadaceae") %>% filter(identity %in% 1.0000000) %>% unique()## # A tibble: 28 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST23 1
## 2 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST12 1
## 3 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST15 1
## 4 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST11 1
## 5 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST13 1
## 6 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST14 1
## 7 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST16 1
## 8 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST17 1
## 9 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST19 1
## 10 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST20 1
## # ℹ 18 more rowsall_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Xanthomonadaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV12 Proteobacteria Xanthomonadaceae Sten… Changins B73 WT 14
## 2 ASV12 Proteobacteria Xanthomonadaceae Sten… Changins B73 bx1 14# 14 strains mapping 100% to ASV8
# other strains not mapping 100%
Xanthomonadaceae_100_id <- all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Xanthomonadaceae") %>% filter(identity %in% 1.0000000) %>% dplyr::select(Strain)
Xanthomonadaceae_100_id <- Xanthomonadaceae_100_id$Strain
all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Xanthomonadaceae") %>% filter(!Strain %in% Xanthomonadaceae_100_id) %>% unique() %>% dplyr::select(Strain) %>% unique() %>% count() ## # A tibble: 2 × 8
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## OTU phylum family genus location background genotype n
## <chr> <chr> <chr> <chr> <fct> <fct> <fct> <int>
## 1 ASV12 Proteobacteria Xanthomonadaceae Sten… Changins B73 WT 9
## 2 ASV12 Proteobacteria Xanthomonadaceae Sten… Changins B73 bx1 9all_phy_psmelt_iso_BX_identity_strains %>% filter(family %in% "Xanthomonadaceae") %>%
filter(!Strain %in% Xanthomonadaceae_100_id) %>%
unique() %>%
dplyr::arrange(Strain)## # A tibble: 18 × 9
## # Groups: OTU, phylum, family, genus, location, background, genotype [2]
## phylum genus location background genotype OTU family Strain identity
## <chr> <chr> <fct> <fct> <fct> <chr> <chr> <chr> <dbl>
## 1 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST18 0.987
## 2 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST18 0.987
## 3 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST21 0.989
## 4 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST21 0.989
## 5 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST22 0.997
## 6 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST22 0.997
## 7 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST28 0.989
## 8 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST28 0.989
## 9 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST52 0.989
## 10 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST52 0.989
## 11 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST521 0.989
## 12 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST521 0.989
## 13 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST61 0.989
## 14 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST61 0.989
## 15 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST72 0.989
## 16 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST72 0.989
## 17 Proteobacter… Sten… Changins B73 WT ASV12 Xanth… LST82 0.989
## 18 Proteobacter… Sten… Changins B73 bx1 ASV12 Xanth… LST82 0.989# Other families
iso.tab_id <- iso.tab %>% dplyr::rename(identity = '%')
iso.tab_id %>% filter(Strain %in% "LMN1") %>% filter(identity %in% 1.0000000) %>% unique()## identity Strain ASV
## 1 1 LMN1 ASV2934
## 2 1 LMN1 ASV8576
## 3 1 LMN1 ASV11112# % Strain ASV
# 1 1.0000000 LMN1 ASV2934
# 3 1.0000000 LMN1 ASV8576
# 5 1.0000000 LMN1 ASV11112
iso.tab_id %>% filter(Strain %in% "LMN1") %>% unique()## identity Strain ASV
## 1 1.0000000 LMN1 ASV2934
## 2 0.9927361 LMN1 ASV5661
## 3 1.0000000 LMN1 ASV8576
## 4 0.9927361 LMN1 ASV9108
## 5 1.0000000 LMN1 ASV11112# identity Strain ASV
# 1 1.0000000 LMN1 ASV2934
# 2 0.9927361 LMN1 ASV5661
# 3 1.0000000 LMN1 ASV8576
# 4 0.9927361 LMN1 ASV9108
# 5 1.0000000 LMN1 ASV11112
iso.tab_id %>% filter(Strain %in% c("LME3", "LMX9231", "LMZ1")) %>% filter(identity %in% 1.0000000) %>% unique() %>%
dplyr::arrange(Strain)## identity Strain ASV
## 1 1 LME3 ASV31
## 2 1 LMX9231 ASV31
## 3 1 LMZ1 ASV31# identity Strain ASV
# 1 1 LME3 ASV31
# 2 1 LMX9231 ASV31
# 3 1 LMZ1 ASV31
iso.tab_id %>% filter(Strain %in% c("LME3", "LMX9231", "LMZ1")) %>% unique() %>%
dplyr::arrange(Strain)## identity Strain ASV
## 1 1.0000000 LME3 ASV31
## 2 0.9708223 LME3 ASV85
## 3 0.9893899 LME3 ASV93
## 4 0.9814324 LME3 ASV190
## 5 0.9708223 LME3 ASV461
## 6 0.9867374 LME3 ASV508
## 7 0.9946950 LME3 ASV518
## 8 0.9734748 LME3 ASV680
## 9 0.9973475 LME3 ASV988
## 10 0.9840849 LME3 ASV1034
## 11 0.9787798 LME3 ASV1570
## 12 0.9761273 LME3 ASV2286
## 13 0.9867374 LME3 ASV2415
## 14 0.9840849 LME3 ASV2875
## 15 0.9920424 LME3 ASV3081
## 16 0.9761905 LME3 ASV3214
## 17 0.9761273 LME3 ASV3241
## 18 0.9787798 LME3 ASV3258
## 19 0.9761273 LME3 ASV3270
## 20 0.9814324 LME3 ASV3331
## 21 0.9973475 LME3 ASV3491
## 22 0.9920424 LME3 ASV3745
## 23 0.9788360 LME3 ASV4046
## 24 0.9782609 LME3 ASV4579
## 25 0.9782609 LME3 ASV4763
## 26 0.9787798 LME3 ASV5123
## 27 0.9734748 LME3 ASV6307
## 28 0.9814815 LME3 ASV6451
## 29 0.9787798 LME3 ASV6550
## 30 0.9708223 LME3 ASV7411
## 31 0.9893899 LME3 ASV7445
## 32 0.9893899 LME3 ASV7523
## 33 0.9867374 LME3 ASV7530
## 34 0.9841270 LME3 ASV7754
## 35 0.9840849 LME3 ASV8519
## 36 0.9787798 LME3 ASV8832
## 37 0.9867374 LME3 ASV8954
## 38 0.9840849 LME3 ASV10456
## 39 0.9973475 LME3 ASV10722
## 40 0.9734748 LME3 ASV11380
## 41 0.9758454 LME3 ASV12901
## 42 0.9973475 LME3 ASV14980
## 43 0.9758454 LME3 ASV15171
## 44 0.9735450 LME3 ASV15334
## 45 0.9806763 LME3 ASV15530
## 46 0.9787798 LME3 ASV16109
## 47 0.9867374 LME3 ASV16491
## 48 0.9758454 LME3 ASV17105
## 49 1.0000000 LMX9231 ASV31
## 50 0.9708223 LMX9231 ASV85
## 51 0.9893899 LMX9231 ASV93
## 52 0.9814324 LMX9231 ASV190
## 53 0.9708223 LMX9231 ASV461
## 54 0.9867374 LMX9231 ASV508
## 55 0.9946950 LMX9231 ASV518
## 56 0.9734748 LMX9231 ASV680
## 57 0.9973475 LMX9231 ASV988
## 58 0.9840849 LMX9231 ASV1034
## 59 0.9787798 LMX9231 ASV1570
## 60 0.9761273 LMX9231 ASV2286
## 61 0.9867374 LMX9231 ASV2415
## 62 0.9840849 LMX9231 ASV2875
## 63 0.9920424 LMX9231 ASV3081
## 64 0.9761905 LMX9231 ASV3214
## 65 0.9761273 LMX9231 ASV3241
## 66 0.9787798 LMX9231 ASV3258
## 67 0.9761273 LMX9231 ASV3270
## 68 0.9814324 LMX9231 ASV3331
## 69 0.9973475 LMX9231 ASV3491
## 70 0.9920424 LMX9231 ASV3745
## 71 0.9788360 LMX9231 ASV4046
## 72 0.9782609 LMX9231 ASV4579
## 73 0.9782609 LMX9231 ASV4763
## 74 0.9787798 LMX9231 ASV5123
## 75 0.9734748 LMX9231 ASV6307
## 76 0.9814815 LMX9231 ASV6451
## 77 0.9787798 LMX9231 ASV6550
## 78 0.9708223 LMX9231 ASV7411
## 79 0.9893899 LMX9231 ASV7445
## 80 0.9893899 LMX9231 ASV7523
## 81 0.9867374 LMX9231 ASV7530
## 82 0.9841270 LMX9231 ASV7754
## 83 0.9840849 LMX9231 ASV8519
## 84 0.9787798 LMX9231 ASV8832
## 85 0.9867374 LMX9231 ASV8954
## 86 0.9840849 LMX9231 ASV10456
## 87 0.9973475 LMX9231 ASV10722
## 88 0.9734748 LMX9231 ASV11380
## 89 0.9758454 LMX9231 ASV12901
## 90 0.9973475 LMX9231 ASV14980
## 91 0.9758454 LMX9231 ASV15171
## 92 0.9735450 LMX9231 ASV15334
## 93 0.9806763 LMX9231 ASV15530
## 94 0.9787798 LMX9231 ASV16109
## 95 0.9867374 LMX9231 ASV16491
## 96 0.9758454 LMX9231 ASV17105
## 97 1.0000000 LMZ1 ASV31
## 98 0.9761273 LMZ1 ASV85
## 99 0.9946950 LMZ1 ASV93
## 100 0.9867374 LMZ1 ASV190
## 101 0.9761273 LMZ1 ASV461
## 102 0.9920424 LMZ1 ASV508
## 103 0.9946950 LMZ1 ASV518
## 104 0.9787798 LMZ1 ASV680
## 105 0.9973475 LMZ1 ASV988
## 106 0.9893899 LMZ1 ASV1034
## 107 0.9734748 LMZ1 ASV1110
## 108 0.9787798 LMZ1 ASV1570
## 109 0.9734748 LMZ1 ASV2156
## 110 0.9814324 LMZ1 ASV2286
## 111 0.9708223 LMZ1 ASV2339
## 112 0.9867374 LMZ1 ASV2415
## 113 0.9893899 LMZ1 ASV2875
## 114 0.9734748 LMZ1 ASV2941
## 115 0.9920424 LMZ1 ASV3081
## 116 0.9761905 LMZ1 ASV3214
## 117 0.9761273 LMZ1 ASV3241
## 118 0.9840849 LMZ1 ASV3258
## 119 0.9814324 LMZ1 ASV3270
## 120 0.9867374 LMZ1 ASV3331
## 121 0.9973475 LMZ1 ASV3491
## 122 0.9920424 LMZ1 ASV3745
## 123 0.9788360 LMZ1 ASV4046
## 124 0.9782609 LMZ1 ASV4579
## 125 0.9782609 LMZ1 ASV4763
## 126 0.9814324 LMZ1 ASV5123
## 127 0.9761273 LMZ1 ASV6307
## 128 0.9814815 LMZ1 ASV6451
## 129 0.9840849 LMZ1 ASV6550
## 130 0.9761273 LMZ1 ASV7411
## 131 0.9893899 LMZ1 ASV7445
## 132 0.9893899 LMZ1 ASV7523
## 133 0.9920424 LMZ1 ASV7530
## 134 0.9841270 LMZ1 ASV7754
## 135 0.9840849 LMZ1 ASV8519
## 136 0.9840849 LMZ1 ASV8832
## 137 0.9867374 LMZ1 ASV8954
## 138 0.9708995 LMZ1 ASV10221
## 139 0.9893899 LMZ1 ASV10456
## 140 0.9973475 LMZ1 ASV10722
## 141 0.9761273 LMZ1 ASV11380
## 142 0.9758454 LMZ1 ASV12901
## 143 0.9973475 LMZ1 ASV14980
## 144 0.9806763 LMZ1 ASV15171
## 145 0.9735450 LMZ1 ASV15334
## 146 0.9855072 LMZ1 ASV15530
## 147 0.9787798 LMZ1 ASV16109
## 148 0.9920424 LMZ1 ASV16491
## 149 0.9758454 LMZ1 ASV17105
## 150 0.9710145 LMZ1 ASV20663
## 151 0.9710145 LMZ1 ASV24304iso.tab_id %>% filter(Strain %in% c("LMC1", "LMK1")) %>% filter(identity %in% 1.0000000) %>% unique() %>%
dplyr::arrange(Strain)## identity Strain ASV
## 1 1 LMC1 ASV377
## 2 1 LMK1 ASV377# identity Strain ASV
# 1 1 LMC1 ASV377
# 2 1 LMK1 ASV377
#ASV474
iso.tab_id %>% filter(Strain %in% c("LAC11")) %>% filter(identity %in% 1.0000000) %>% unique()## identity Strain ASV
## 1 1 LAC11 ASV20338# identity Strain ASV
# 1 1 LAC11 ASV20338
iso.tab_id %>% filter(Strain %in% c("LML1")) %>% filter(identity %in% 1.0000000) %>% unique() %>%
dplyr::arrange(Strain)## [1] identity Strain ASV
## <0 rows> (or 0-length row.names)# identity Strain ASV
# 1 0.9973545 LML1 ASV2632
selected_ASVs <- c("ASV2934", "ASV31", "ASV474", "ASV20338", "ASV2632", "ASV1078", "ASV1322", "ASV1182", "ASV105", "ASV972", "ASV267", "ASV107", "ASV4", "ASV340", "ASV8", "ASV1000", "ASV3", "ASV538", "ASV1521", "ASV12")Selection: highest similarity ASV1078 Microbacteriaceae ASV1322
Bacillaceae ASV1182 Bacillaceae (LMJ1, LMX1, LMX8) ASV105 Micrococcaceae
ASV972 Micrococcaceae (LAR12) ASV267 Oxalobacteraceae LMU1 ASV107
Oxalobacteraceae LMS1 ASV4 Pseudomonadaceae ASV340 Pseudomonadaceae LMY1
ASV8 Rhizobiaceae ASV1000 Rhizobiaceae (LMQ1) ASV3 Sphingomonadaceae
ASV538 Streptomycetaceae (LMF1) ASV1521 Streptomycetaceae (LMG1, LMG2)
ASV12 Xanthomonadaceae ASV2632 LML1
ASV20338 LAC11 ASV474 LMC1 LMK1 ASV2934 LMN1
#write_rds(all_phy_psmelt_iso_BX_abundance, "../Output/II_Field_soils/all_phy_psmelt_iso_BX_abundance.rds")ASV_WTbx1dif_OTU <- all_phy_psmelt_iso_BX_abundance %>% filter(OTU %in% selected_ASVs) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = WTbx1dif, x = interaction(family, OTU))) +
geom_boxplot(aes(color = family)) +
geom_jitter(aes(color=family), show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ compartment) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
ASV_WTbx1dif_OTU
ASV_abundance_OTU <- all_phy_psmelt_iso_BX_abundance %>% filter(OTU %in% selected_ASVs) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = WT, x = interaction(family, OTU))) +
geom_boxplot(aes(color = family)) +
geom_jitter(aes(color=family), show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ compartment) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
ASV_abundance_OTU
all_phy_psmelt_iso_BX_abundance %<>% mutate(WTbx1dif_weigh_WT = WTbx1dif * WT)
ASV_weighed_BX_abundance_OTU <- all_phy_psmelt_iso_BX_abundance %>% filter(OTU %in% selected_ASVs) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = WTbx1dif_weigh_WT, x = interaction(family, OTU))) +
geom_boxplot(aes(color = family)) +
geom_jitter(aes(color=family), show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ compartment) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
ASV_weighed_BX_abundance_OTU
ASV_log2FC_OTU <- all_phy_psmelt_iso_BX_abundance %>% filter(OTU %in% selected_ASVs) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("rhizo", "root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(y = log2FC, x = interaction(family, OTU))) +
geom_boxplot(aes(color = family)) +
geom_jitter(aes(color=family), show.legend = TRUE) +
geom_hline(yintercept = 0) +
coord_flip() +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ compartment) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
ASV_log2FC_OTU
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(OTU %in% selected_ASVs) %>%
filter(compartment %in% "root") %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter(width = 0.1)+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.8) +
facet_wrap(family~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% c("LME3", "LMX9231", "LMZ1")) %>%
filter(compartment %in% "root") %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter(width = 0.1)+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.8) +
facet_wrap(family~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% c("LMN1")) %>%
filter(compartment %in% "root") %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter(width = 0.1)+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.8) +
facet_wrap(family~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% c("LAC11")) %>%
filter(compartment %in% "root") %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter(width = 0.1)+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.8) +
facet_wrap(family~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% c("LMC1", "LMK1")) %>%
filter(compartment %in% "root") %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter(width = 0.1)+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.8) +
facet_wrap(family~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% c("LML1")) %>%
filter(compartment %in% "root") %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter(width = 0.1)+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.8) +
facet_wrap(family~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX_abundance %>% filter(compartment %in% c("rhizo", "root")) %>% filter(location %in% "Changins") %>% filter(family %in% c("Chitinophagaceae", "Deinococcaceae", "Moraxellaceae", "Nocardioidaceae", "Sphingobacteriaceae"))## # A tibble: 720 × 16
## OTU rep phylum family genus location background compartment bx1 WT
## <chr> <dbl> <chr> <chr> <chr> <fct> <fct> <fct> <dbl> <dbl>
## 1 ASV2… 2 Bacte… Chiti… Chit… Changins B73 rhizo 0.0459 0
## 2 ASV8… 7 Bacte… Chiti… Chit… Changins B73 rhizo 0 0.0179
## 3 ASV1… 8 Bacte… Chiti… Chit… Changins B73 rhizo 0 0
## 4 ASV1… 1 Bacte… Chiti… Chit… Changins B73 rhizo 0 0
## 5 ASV1… 3 Bacte… Chiti… Chit… Changins B73 rhizo 0 0
## 6 ASV1… 5 Bacte… Chiti… Chit… Changins B73 root 0 0
## 7 ASV1… 6 Bacte… Chiti… Chit… Changins B73 root 0 0
## 8 ASV1… 6 Bacte… Chiti… Chit… Changins B73 rhizo 0 0
## 9 ASV1… 7 Bacte… Chiti… Chit… Changins B73 rhizo 0 0
## 10 ASV1… 3 Bacte… Chiti… Chit… Changins B73 root 0 0
## # ℹ 710 more rows
## # ℹ 6 more variables: BXcol <dbl>, log2FC <dbl>, WTbx1dif <dbl>,
## # WTbx1dif_zscore <dbl>, Strain <chr>, WTbx1dif_weigh_WT <dbl>#write_rds(all_phy_psmelt_iso_BX_abundance_meanOTU, "../Output/II_Field_soils/all_phy_psmelt_iso_BX_abundance_meanOTU.rds")all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(!family %in% c("Chitinophagaceae", "Deinococcaceae", "Moraxellaceae", "Nocardioidaceae", "Sphingobacteriaceae", "Planococcaceae")) %>%
filter(compartment %in% "root") %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
# geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.1) +
facet_wrap(~family, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(!family %in% c("Chitinophagaceae", "Deinococcaceae", "Moraxellaceae", "Nocardioidaceae", "Sphingobacteriaceae", "Planococcaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~family, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(!family %in% c("Chitinophagaceae", "Deinococcaceae", "Moraxellaceae", "Nocardioidaceae", "Sphingobacteriaceae", "Planococcaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~family, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()
only for well represented OTUs
all_phy_psmelt_iso_BX %>% filter(OTU %in% represented_OTU) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
dplyr::select(-Strain) %>%
distinct() %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y = 4) +
facet_wrap(~family, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ family) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
all_phy_psmelt_iso_BX %>% filter(OTU %in% represented_OTU) %>%
filter(Strain %in% strains) %>%
filter(compartment %in% c("root")) %>%
# filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
# mutate(log2FC = replace(log2FC, log2FC == -Inf, -5)) %>%
# mutate(log2FC = replace(log2FC, log2FC == Inf, 5)) %>%
# filter(!WTbx1dif %in% 0) %>%
dplyr::select(-Strain) %>%
distinct() %>%
# filter(!log2FC %in% c(NA, NaN)) %>%
mutate(compartment = factor(compartment, levels = c("root", "rhizo") )) %>%
mutate(OTU = reorder(OTU, desc(family))) %>%
# ggplot(aes(y = log2FC, x = reorder(interaction(family, OTU), desc(family)))) +
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
# geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y = 4) +
facet_wrap(~family, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +f
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family)+
facet_wrap(~ OTU) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
## # A tibble: 58 × 11
## OTU family .y. group1 group2 n1 n2 statistic df p p.signif
## <chr> <chr> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <chr>
## 1 ASV100 Strep… Abun… WT bx1 10 7 -0.139 14.5 0.891 ns
## 2 ASV10… Rhizo… Abun… WT bx1 10 7 -1.50 6.55 0.18 ns
## 3 ASV10… Pseud… Abun… WT bx1 10 7 1.33 9 0.217 ns
## 4 ASV105 Micro… Abun… WT bx1 10 7 0.644 14.6 0.53 ns
## 5 ASV107 Burkh… Abun… WT bx1 10 7 -0.786 12.4 0.447 ns
## 6 ASV10… Micro… Abun… WT bx1 10 7 0.399 15.0 0.696 ns
## 7 ASV11… Bacil… Abun… WT bx1 10 7 0.517 9.20 0.617 ns
## 8 ASV12 Xanth… Abun… WT bx1 10 7 -2.26 8.89 0.0507 ns
## 9 ASV13… Strep… Abun… WT bx1 10 7 1.25 11.7 0.237 ns
## 10 ASV13… Bacil… Abun… WT bx1 10 7 0.0874 12.9 0.932 ns
## # ℹ 48 more rows| OTU | family | .y. | group1 | group2 | n1 | n2 | statistic | df | p | p.signif |
|---|---|---|---|---|---|---|---|---|---|---|
| ASV100 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | -0.1392077 | 14.543635 | 0.8910 | ns |
| ASV1000 | Rhizobiaceae | Abundance | WT | bx1 | 10 | 7 | -1.5023458 | 6.549283 | 0.1800 | ns |
| ASV1014 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | 1.3283246 | 9.000000 | 0.2170 | ns |
| ASV105 | Micrococcaceae | Abundance | WT | bx1 | 10 | 7 | 0.6436429 | 14.582456 | 0.5300 | ns |
| ASV107 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -0.7857060 | 12.448290 | 0.4470 | ns |
| ASV1078 | Microbacteriaceae | Abundance | WT | bx1 | 10 | 7 | 0.3989153 | 14.992563 | 0.6960 | ns |
| ASV1182 | Bacillaceae | Abundance | WT | bx1 | 10 | 7 | 0.5168119 | 9.196489 | 0.6170 | ns |
| ASV12 | Xanthomonadaceae | Abundance | WT | bx1 | 10 | 7 | -2.2574405 | 8.889978 | 0.0507 | ns |
| ASV1317 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | 1.2451919 | 11.743739 | 0.2370 | ns |
| ASV1322 | Bacillaceae | Abundance | WT | bx1 | 10 | 7 | 0.0874425 | 12.893131 | 0.9320 | ns |
| ASV1520 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | 0.5550099 | 12.378853 | 0.5890 | ns |
| ASV1521 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | 0.9561018 | 12.248690 | 0.3580 | ns |
| ASV159 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | 0.5181715 | 14.863072 | 0.6120 | ns |
| ASV1598 | Microbacteriaceae | Abundance | WT | bx1 | 10 | 7 | 0.8778713 | 12.874211 | 0.3960 | ns |
| ASV1656 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -1.8921740 | 10.716893 | 0.0858 | ns |
| ASV1708 | Bacillaceae | Abundance | WT | bx1 | 10 | 7 | 1.2475584 | 14.997160 | 0.2310 | ns |
| ASV189 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | 2.0702932 | 9.000000 | 0.0683 | ns |
| ASV190 | Enterobacteriaceae | Abundance | WT | bx1 | 10 | 7 | -2.0058910 | 6.000000 | 0.0917 | ns |
| ASV2397 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | 1.1360517 | 9.120507 | 0.2850 | ns |
| ASV247 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -1.0861733 | 14.367953 | 0.2950 | ns |
| ASV2489 | Bacillaceae | Abundance | WT | bx1 | 10 | 7 | 0.6073955 | 14.661779 | 0.5530 | ns |
| ASV2524 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | 1.2850607 | 10.853675 | 0.2260 | ns |
| ASV2596 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | -0.6733819 | 8.531024 | 0.5190 | ns |
| ASV265 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | -1.0905850 | 6.979829 | 0.3120 | ns |
| ASV267 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -1.5440474 | 9.278433 | 0.1560 | ns |
| ASV2957 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | 1.5744765 | 9.000000 | 0.1500 | ns |
| ASV3 | Sphingomonadaceae | Abundance | WT | bx1 | 10 | 7 | -0.2024577 | 9.060357 | 0.8440 | ns |
| ASV307 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | -1.6130220 | 6.000000 | 0.1580 | ns |
| ASV31 | Enterobacteriaceae | Abundance | WT | bx1 | 10 | 7 | 0.8464223 | 9.708483 | 0.4180 | ns |
| ASV33 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | -1.2126796 | 6.789729 | 0.2660 | ns |
| ASV3305 | Rhizobiaceae | Abundance | WT | bx1 | 10 | 7 | -1.7221028 | 6.000000 | 0.1360 | ns |
| ASV340 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | -1.2898411 | 9.679773 | 0.2270 | ns |
| ASV356 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -1.5992159 | 6.686604 | 0.1560 | ns |
| ASV3604 | Bacillaceae | Abundance | WT | bx1 | 10 | 7 | 2.2829011 | 11.378419 | 0.0426 | * |
| ASV382 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | 1.0820752 | 13.334704 | 0.2980 | ns |
| ASV3840 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | -2.3688763 | 7.355095 | 0.0480 | * |
| ASV4 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | -1.8692910 | 14.779464 | 0.0815 | ns |
| ASV4167 | Rhizobiaceae | Abundance | WT | bx1 | 10 | 7 | -1.5947171 | 6.000000 | 0.1620 | ns |
| ASV429 | Bacillaceae | Abundance | WT | bx1 | 10 | 7 | 1.7571157 | 13.007608 | 0.1020 | ns |
| ASV452 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -1.8269977 | 7.488471 | 0.1080 | ns |
| ASV474 | Enterobacteriaceae | Abundance | WT | bx1 | 10 | 7 | -1.0165833 | 6.009969 | 0.3490 | ns |
| ASV4742 | Bacillaceae | Abundance | WT | bx1 | 10 | 7 | 0.8086108 | 14.938788 | 0.4310 | ns |
| ASV49 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | 0.9840583 | 13.425266 | 0.3420 | ns |
| ASV538 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | 0.5071189 | 10.571477 | 0.6220 | ns |
| ASV54 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | 0.1915853 | 13.015987 | 0.8510 | ns |
| ASV64 | Streptomycetaceae | Abundance | WT | bx1 | 10 | 7 | -0.0158238 | 14.462151 | 0.9880 | ns |
| ASV6737 | Rhizobiaceae | Abundance | WT | bx1 | 10 | 7 | -1.8001242 | 6.000000 | 0.1220 | ns |
| ASV7206 | Microbacteriaceae | Abundance | WT | bx1 | 10 | 7 | 0.3040182 | 14.555296 | 0.7650 | ns |
| ASV784 | Sphingomonadaceae | Abundance | WT | bx1 | 10 | 7 | -0.6731601 | 12.427637 | 0.5130 | ns |
| ASV8 | Rhizobiaceae | Abundance | WT | bx1 | 10 | 7 | -1.5899502 | 6.253949 | 0.1610 | ns |
| ASV8270 | Microbacteriaceae | Abundance | WT | bx1 | 10 | 7 | 1.1474530 | 9.440767 | 0.2790 | ns |
| ASV85 | Enterobacteriaceae | Abundance | WT | bx1 | 10 | 7 | -0.9901076 | 6.018042 | 0.3600 | ns |
| ASV883 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | 1.7366280 | 9.000000 | 0.1160 | ns |
| ASV914 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -0.8717046 | 8.814160 | 0.4060 | ns |
| ASV917 | Burkholderiaceae | Abundance | WT | bx1 | 10 | 7 | -0.2791383 | 12.895426 | 0.7850 | ns |
| ASV968 | Microbacteriaceae | Abundance | WT | bx1 | 10 | 7 | 1.2847997 | 14.995394 | 0.2180 | ns |
| ASV972 | Micrococcaceae | Abundance | WT | bx1 | 10 | 7 | 1.9028076 | 11.574134 | 0.0822 | ns |
| ASV979 | Pseudomonadaceae | Abundance | WT | bx1 | 10 | 7 | 1.6930583 | 9.000000 | 0.1250 | ns |
all_phy_psmelt_iso_BX %>% filter(OTU %in% represented_OTU) %>%
filter(Strain %in% strains) %>%
dplyr::select(-Strain) %>%
filter(compartment %in% c("root")) %>%
filter(location %in% "Changins") %>%
filter(OTU %in% "ASV4") %>%
distinct() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT") +
facet_wrap(~family, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
# scale_shape_manual(values=c(15, 16, 17, 18)) +
scale_color_manual(values = all_phy_psmelt_iso_BX_abundance_meanOTU_level_cols_family) +
facet_wrap(~ OTU) +
#theme(axis.title.y = element_text(size = rel(0.5)))+
labs(x = "",
y = "WT - bx1",
shape = "compartment")
Bacillaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Bacillaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Bacillaceae")
Burkholderiaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Burkholderiaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Burkholderiaceae")
Enterobacteriaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Enterobacteriaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Enterobacteriaceae")
Pseudomonadaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Pseudomonadaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Pseudomonadaceae")
Streptomycetaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Streptomycetaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()+
labs(title = "Streptomycetaceae")
Spingomonadaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Sphingomonadaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw()+
labs(title = "Sphingomonadaceae")
Rhizobiaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Rhizobiaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Rhizobiaceae")
Xanthomonadaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Xanthomonadaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Xanthomonadaceae")
Microbacteriaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Microbacteriaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Microbacteriaceae")
Micrococcaceae
all_phy_psmelt_iso_BX %>% filter(location %in% "Changins") %>%
filter(Strain %in% strains) %>%
filter(family %in% c("Micrococcaceae")) %>%
filter(compartment %in% "root") %>%
filter(Abundance > 0.1) %>%
dplyr::select(OTU, family, Abundance, genotype) %>%
unique() %>%
ggplot(aes(x=genotype, y = Abundance))+
geom_bar(aes(fill = genotype), stat = "summary") +
geom_jitter()+
# stat_compare_means(method = "anova", aes(x = genotype, y = Abundance), label.y.npc = 0.02, label.x.npc = 0.6) +
stat_compare_means(label = "p.signif", method = "t.test", ref.group = "WT", label.y.npc = 0.6) +
facet_wrap(~OTU, scales = "free_y") +
scale_fill_manual(values = c("gold", "forestgreen")) +
theme_bw() +
labs(title = "Micrococcaceae")
Cumulative field abundance isolates
sum all relative abundances in total of all represented ASVs
all_phy_psmelt_BX_abundance_meanOTU_mapped <- all_phy_psmelt_iso_BX_abundance_meanOTU %>% as.data.frame() %>% dplyr::select(-OTU, -Strain) %>% unique()
all_phy_psmelt_mean <- all_phy_psmelt %>%
dplyr::select(-rep) %>%
group_by(OTU, compartment, location, background, genotype) %>% dplyr::summarise(mean_abundance = mean(Abundance))
# Total microbiome (no mapping)
total_abundance <- all_phy_psmelt_mean %>%
group_by(location, background, compartment, genotype) %>%
dplyr::summarise(sum_abundance = sum(mean_abundance)) # 99.96 % of the relative abundance
total_abundance_map_ASV <- all_phy_psmelt_BX_abundance_meanOTU_mapped %>% group_by(location, background, compartment) %>%
dplyr::summarise(sum_abundance = sum(WT_mean))
total_abundance_map_ASV_family <- all_phy_psmelt_BX_abundance_meanOTU_mapped %>% group_by(location, background, compartment, family) %>%
dplyr::summarise(sum_abundance = sum(WT_mean))
total_abundance_map_ASV_family %>% filter(family %in% "Pseudomonadaceae")## # A tibble: 12 × 5
## # Groups: location, background, compartment [12]
## location background compartment family sum_abundance
## <fct> <fct> <fct> <chr> <dbl>
## 1 Changins B73 rhizo Pseudomonadaceae 2.12
## 2 Changins B73 root Pseudomonadaceae 2.77
## 3 Ithaca W22 soil Pseudomonadaceae 0.180
## 4 Ithaca W22 rhizo Pseudomonadaceae 0.727
## 5 Ithaca W22 root Pseudomonadaceae 1.83
## 6 Zurich B73 soil Pseudomonadaceae 0
## 7 Zurich B73 rhizo Pseudomonadaceae 25.8
## 8 Zurich B73 root Pseudomonadaceae 19.3
## 9 Zurich W22 soil Pseudomonadaceae 0
## 10 Zurich W22 rhizo Pseudomonadaceae 12.2
## 11 Zurich W22 root Pseudomonadaceae 9.29
## 12 Sheffield W22 root Pseudomonadaceae 0.506total_abundance_map_ASV_family %>% filter(family %in% "Sphingomonadaceae")## # A tibble: 12 × 5
## # Groups: location, background, compartment [12]
## location background compartment family sum_abundance
## <fct> <fct> <fct> <chr> <dbl>
## 1 Changins B73 rhizo Sphingomonadaceae 0.547
## 2 Changins B73 root Sphingomonadaceae 0.701
## 3 Ithaca W22 soil Sphingomonadaceae 1.47
## 4 Ithaca W22 rhizo Sphingomonadaceae 6.94
## 5 Ithaca W22 root Sphingomonadaceae 3.27
## 6 Zurich B73 soil Sphingomonadaceae 0.0592
## 7 Zurich B73 rhizo Sphingomonadaceae 0.371
## 8 Zurich B73 root Sphingomonadaceae 1.19
## 9 Zurich W22 soil Sphingomonadaceae 0.0445
## 10 Zurich W22 rhizo Sphingomonadaceae 0.662
## 11 Zurich W22 root Sphingomonadaceae 0.676
## 12 Sheffield W22 root Sphingomonadaceae 0total_abundance_map_ASV_family %>% filter(location %in% "Changins") %>% filter(compartment %in% "root") %>% dplyr::arrange(desc(sum_abundance))## # A tibble: 18 × 5
## # Groups: location, background, compartment [1]
## location background compartment family sum_abundance
## <fct> <fct> <fct> <chr> <dbl>
## 1 Changins B73 root Streptomycetaceae 14.2
## 2 Changins B73 root Oxalobacteraceae 5.22
## 3 Changins B73 root Pseudomonadaceae 2.77
## 4 Changins B73 root Bacillaceae 1.34
## 5 Changins B73 root Enterobacteriaceae 1.28
## 6 Changins B73 root Rhizobiaceae 0.919
## 7 Changins B73 root Sphingomonadaceae 0.701
## 8 Changins B73 root Microbacteriaceae 0.560
## 9 Changins B73 root Micrococcaceae 0.457
## 10 Changins B73 root Xanthomonadaceae 0.248
## 11 Changins B73 root Weeksellaceae 0.186
## 12 Changins B73 root Paenibacillaceae 0.0445
## 13 Changins B73 root Chitinophagaceae 0
## 14 Changins B73 root Deinococcaceae 0
## 15 Changins B73 root Moraxellaceae 0
## 16 Changins B73 root Nocardioidaceae 0
## 17 Changins B73 root Planococcaceae 0
## 18 Changins B73 root Sphingobacteriaceae 0total_abundance_map_ASV_family %>% filter(location %in% "Ithaca") %>% filter(compartment %in% "root") %>% dplyr::arrange(desc(sum_abundance))## # A tibble: 18 × 5
## # Groups: location, background, compartment [1]
## location background compartment family sum_abundance
## <fct> <fct> <fct> <chr> <dbl>
## 1 Ithaca W22 root Sphingomonadaceae 3.27
## 2 Ithaca W22 root Streptomycetaceae 3.06
## 3 Ithaca W22 root Enterobacteriaceae 2.87
## 4 Ithaca W22 root Rhizobiaceae 2.27
## 5 Ithaca W22 root Oxalobacteraceae 1.89
## 6 Ithaca W22 root Pseudomonadaceae 1.83
## 7 Ithaca W22 root Bacillaceae 0.764
## 8 Ithaca W22 root Xanthomonadaceae 0.673
## 9 Ithaca W22 root Microbacteriaceae 0.629
## 10 Ithaca W22 root Micrococcaceae 0.249
## 11 Ithaca W22 root Nocardioidaceae 0.0594
## 12 Ithaca W22 root Weeksellaceae 0.0508
## 13 Ithaca W22 root Chitinophagaceae 0.0321
## 14 Ithaca W22 root Sphingobacteriaceae 0.00754
## 15 Ithaca W22 root Moraxellaceae 0.00754
## 16 Ithaca W22 root Deinococcaceae 0.00598
## 17 Ithaca W22 root Paenibacillaceae 0
## 18 Ithaca W22 root Planococcaceae 0total_abundance_map_ASV_family %>% filter(location %in% "Zurich") %>% filter(compartment %in% "root") %>% filter(background %in% "B73") %>% dplyr::arrange(desc(sum_abundance))## # A tibble: 18 × 5
## # Groups: location, background, compartment [1]
## location background compartment family sum_abundance
## <fct> <fct> <fct> <chr> <dbl>
## 1 Zurich B73 root Pseudomonadaceae 19.3
## 2 Zurich B73 root Enterobacteriaceae 13.6
## 3 Zurich B73 root Oxalobacteraceae 4.53
## 4 Zurich B73 root Xanthomonadaceae 3.60
## 5 Zurich B73 root Rhizobiaceae 1.98
## 6 Zurich B73 root Weeksellaceae 1.22
## 7 Zurich B73 root Microbacteriaceae 1.21
## 8 Zurich B73 root Sphingomonadaceae 1.19
## 9 Zurich B73 root Micrococcaceae 0.361
## 10 Zurich B73 root Sphingobacteriaceae 0.00772
## 11 Zurich B73 root Bacillaceae 0
## 12 Zurich B73 root Chitinophagaceae 0
## 13 Zurich B73 root Deinococcaceae 0
## 14 Zurich B73 root Moraxellaceae 0
## 15 Zurich B73 root Nocardioidaceae 0
## 16 Zurich B73 root Paenibacillaceae 0
## 17 Zurich B73 root Planococcaceae 0
## 18 Zurich B73 root Streptomycetaceae 0total_abundance_map_ASV_family %>% filter(location %in% "Sheffield") %>% filter(compartment %in% "root") %>% dplyr::arrange(desc(sum_abundance))## # A tibble: 18 × 5
## # Groups: location, background, compartment [1]
## location background compartment family sum_abundance
## <fct> <fct> <fct> <chr> <dbl>
## 1 Sheffield W22 root Bacillaceae 2.16
## 2 Sheffield W22 root Micrococcaceae 0.989
## 3 Sheffield W22 root Oxalobacteraceae 0.871
## 4 Sheffield W22 root Streptomycetaceae 0.848
## 5 Sheffield W22 root Pseudomonadaceae 0.506
## 6 Sheffield W22 root Microbacteriaceae 0.387
## 7 Sheffield W22 root Paenibacillaceae 0.0841
## 8 Sheffield W22 root Weeksellaceae 0.0253
## 9 Sheffield W22 root Planococcaceae 0.0165
## 10 Sheffield W22 root Rhizobiaceae 0.0159
## 11 Sheffield W22 root Sphingobacteriaceae 0.0118
## 12 Sheffield W22 root Xanthomonadaceae 0.0102
## 13 Sheffield W22 root Chitinophagaceae 0.00491
## 14 Sheffield W22 root Nocardioidaceae 0.00323
## 15 Sheffield W22 root Enterobacteriaceae 0.00216
## 16 Sheffield W22 root Deinococcaceae 0
## 17 Sheffield W22 root Moraxellaceae 0
## 18 Sheffield W22 root Sphingomonadaceae 0total_abundance_map_ASV %>% knitr::kable()| location | background | compartment | sum_abundance |
|---|---|---|---|
| Changins | B73 | rhizo | 12.280359 |
| Changins | B73 | root | 27.899834 |
| Ithaca | W22 | soil | 3.964605 |
| Ithaca | W22 | rhizo | 13.465404 |
| Ithaca | W22 | root | 17.667511 |
| Zurich | B73 | soil | 2.598360 |
| Zurich | B73 | rhizo | 34.073580 |
| Zurich | B73 | root | 46.954111 |
| Zurich | W22 | soil | 1.047024 |
| Zurich | W22 | rhizo | 17.188441 |
| Zurich | W22 | root | 24.265725 |
| Sheffield | W22 | root | 5.937331 |
total_abundance_map_ASV_family %>% knitr::kable()| location | background | compartment | family | sum_abundance |
|---|---|---|---|---|
| Changins | B73 | rhizo | Bacillaceae | 0.3207786 |
| Changins | B73 | rhizo | Chitinophagaceae | 0.0017877 |
| Changins | B73 | rhizo | Deinococcaceae | 0.0000000 |
| Changins | B73 | rhizo | Enterobacteriaceae | 0.1292595 |
| Changins | B73 | rhizo | Microbacteriaceae | 0.2288258 |
| Changins | B73 | rhizo | Micrococcaceae | 0.1427051 |
| Changins | B73 | rhizo | Moraxellaceae | 0.0000000 |
| Changins | B73 | rhizo | Nocardioidaceae | 0.0000000 |
| Changins | B73 | rhizo | Oxalobacteraceae | 6.6779195 |
| Changins | B73 | rhizo | Paenibacillaceae | 0.0000000 |
| Changins | B73 | rhizo | Planococcaceae | 0.0000000 |
| Changins | B73 | rhizo | Pseudomonadaceae | 2.1160741 |
| Changins | B73 | rhizo | Rhizobiaceae | 0.2879899 |
| Changins | B73 | rhizo | Sphingobacteriaceae | 0.0000000 |
| Changins | B73 | rhizo | Sphingomonadaceae | 0.5472422 |
| Changins | B73 | rhizo | Streptomycetaceae | 1.5650126 |
| Changins | B73 | rhizo | Weeksellaceae | 0.1012386 |
| Changins | B73 | rhizo | Xanthomonadaceae | 0.1615254 |
| Changins | B73 | root | Bacillaceae | 1.3371543 |
| Changins | B73 | root | Chitinophagaceae | 0.0000000 |
| Changins | B73 | root | Deinococcaceae | 0.0000000 |
| Changins | B73 | root | Enterobacteriaceae | 1.2832625 |
| Changins | B73 | root | Microbacteriaceae | 0.5602443 |
| Changins | B73 | root | Micrococcaceae | 0.4566919 |
| Changins | B73 | root | Moraxellaceae | 0.0000000 |
| Changins | B73 | root | Nocardioidaceae | 0.0000000 |
| Changins | B73 | root | Oxalobacteraceae | 5.2240661 |
| Changins | B73 | root | Paenibacillaceae | 0.0444960 |
| Changins | B73 | root | Planococcaceae | 0.0000000 |
| Changins | B73 | root | Pseudomonadaceae | 2.7664103 |
| Changins | B73 | root | Rhizobiaceae | 0.9194660 |
| Changins | B73 | root | Sphingobacteriaceae | 0.0000000 |
| Changins | B73 | root | Sphingomonadaceae | 0.7008582 |
| Changins | B73 | root | Streptomycetaceae | 14.1732563 |
| Changins | B73 | root | Weeksellaceae | 0.1861579 |
| Changins | B73 | root | Xanthomonadaceae | 0.2477699 |
| Ithaca | W22 | soil | Bacillaceae | 0.2142960 |
| Ithaca | W22 | soil | Chitinophagaceae | 0.0063491 |
| Ithaca | W22 | soil | Deinococcaceae | 0.0000000 |
| Ithaca | W22 | soil | Enterobacteriaceae | 0.0958395 |
| Ithaca | W22 | soil | Microbacteriaceae | 0.0652384 |
| Ithaca | W22 | soil | Micrococcaceae | 0.1796378 |
| Ithaca | W22 | soil | Moraxellaceae | 0.0000000 |
| Ithaca | W22 | soil | Nocardioidaceae | 0.0705006 |
| Ithaca | W22 | soil | Oxalobacteraceae | 0.6441987 |
| Ithaca | W22 | soil | Paenibacillaceae | 0.0000000 |
| Ithaca | W22 | soil | Planococcaceae | 0.0000000 |
| Ithaca | W22 | soil | Pseudomonadaceae | 0.1801450 |
| Ithaca | W22 | soil | Rhizobiaceae | 0.1487701 |
| Ithaca | W22 | soil | Sphingobacteriaceae | 0.0000000 |
| Ithaca | W22 | soil | Sphingomonadaceae | 1.4670004 |
| Ithaca | W22 | soil | Streptomycetaceae | 0.3441257 |
| Ithaca | W22 | soil | Weeksellaceae | 0.1002449 |
| Ithaca | W22 | soil | Xanthomonadaceae | 0.4482592 |
| Ithaca | W22 | rhizo | Bacillaceae | 0.2300738 |
| Ithaca | W22 | rhizo | Chitinophagaceae | 0.0432136 |
| Ithaca | W22 | rhizo | Deinococcaceae | 0.0000000 |
| Ithaca | W22 | rhizo | Enterobacteriaceae | 0.7816973 |
| Ithaca | W22 | rhizo | Microbacteriaceae | 0.1105423 |
| Ithaca | W22 | rhizo | Micrococcaceae | 0.0937915 |
| Ithaca | W22 | rhizo | Moraxellaceae | 0.0000000 |
| Ithaca | W22 | rhizo | Nocardioidaceae | 0.0171670 |
| Ithaca | W22 | rhizo | Oxalobacteraceae | 2.7974533 |
| Ithaca | W22 | rhizo | Paenibacillaceae | 0.0000000 |
| Ithaca | W22 | rhizo | Planococcaceae | 0.0000000 |
| Ithaca | W22 | rhizo | Pseudomonadaceae | 0.7271583 |
| Ithaca | W22 | rhizo | Rhizobiaceae | 0.5021250 |
| Ithaca | W22 | rhizo | Sphingobacteriaceae | 0.0000000 |
| Ithaca | W22 | rhizo | Sphingomonadaceae | 6.9419814 |
| Ithaca | W22 | rhizo | Streptomycetaceae | 0.1030512 |
| Ithaca | W22 | rhizo | Weeksellaceae | 0.1257927 |
| Ithaca | W22 | rhizo | Xanthomonadaceae | 0.9913563 |
| Ithaca | W22 | root | Bacillaceae | 0.7635971 |
| Ithaca | W22 | root | Chitinophagaceae | 0.0321239 |
| Ithaca | W22 | root | Deinococcaceae | 0.0059848 |
| Ithaca | W22 | root | Enterobacteriaceae | 2.8746736 |
| Ithaca | W22 | root | Microbacteriaceae | 0.6290434 |
| Ithaca | W22 | root | Micrococcaceae | 0.2486621 |
| Ithaca | W22 | root | Moraxellaceae | 0.0075401 |
| Ithaca | W22 | root | Nocardioidaceae | 0.0593715 |
| Ithaca | W22 | root | Oxalobacteraceae | 1.8942871 |
| Ithaca | W22 | root | Paenibacillaceae | 0.0000000 |
| Ithaca | W22 | root | Planococcaceae | 0.0000000 |
| Ithaca | W22 | root | Pseudomonadaceae | 1.8272373 |
| Ithaca | W22 | root | Rhizobiaceae | 2.2701051 |
| Ithaca | W22 | root | Sphingobacteriaceae | 0.0075401 |
| Ithaca | W22 | root | Sphingomonadaceae | 3.2679302 |
| Ithaca | W22 | root | Streptomycetaceae | 3.0553280 |
| Ithaca | W22 | root | Weeksellaceae | 0.0508397 |
| Ithaca | W22 | root | Xanthomonadaceae | 0.6732469 |
| Zurich | B73 | soil | Bacillaceae | 0.0000000 |
| Zurich | B73 | soil | Chitinophagaceae | 0.0000000 |
| Zurich | B73 | soil | Deinococcaceae | 0.0000000 |
| Zurich | B73 | soil | Enterobacteriaceae | 0.0000000 |
| Zurich | B73 | soil | Microbacteriaceae | 0.0000000 |
| Zurich | B73 | soil | Micrococcaceae | 0.3898240 |
| Zurich | B73 | soil | Moraxellaceae | 0.0000000 |
| Zurich | B73 | soil | Nocardioidaceae | 0.0000000 |
| Zurich | B73 | soil | Oxalobacteraceae | 1.5261891 |
| Zurich | B73 | soil | Paenibacillaceae | 0.0000000 |
| Zurich | B73 | soil | Planococcaceae | 0.0000000 |
| Zurich | B73 | soil | Pseudomonadaceae | 0.0000000 |
| Zurich | B73 | soil | Rhizobiaceae | 0.0000000 |
| Zurich | B73 | soil | Sphingobacteriaceae | 0.0000000 |
| Zurich | B73 | soil | Sphingomonadaceae | 0.0592192 |
| Zurich | B73 | soil | Streptomycetaceae | 0.5105346 |
| Zurich | B73 | soil | Weeksellaceae | 0.0310713 |
| Zurich | B73 | soil | Xanthomonadaceae | 0.0815217 |
| Zurich | B73 | rhizo | Bacillaceae | 0.1898894 |
| Zurich | B73 | rhizo | Chitinophagaceae | 0.0047197 |
| Zurich | B73 | rhizo | Deinococcaceae | 0.0000000 |
| Zurich | B73 | rhizo | Enterobacteriaceae | 0.7215536 |
| Zurich | B73 | rhizo | Microbacteriaceae | 0.1998122 |
| Zurich | B73 | rhizo | Micrococcaceae | 2.1926300 |
| Zurich | B73 | rhizo | Moraxellaceae | 0.0000000 |
| Zurich | B73 | rhizo | Nocardioidaceae | 0.0000000 |
| Zurich | B73 | rhizo | Oxalobacteraceae | 1.3956039 |
| Zurich | B73 | rhizo | Paenibacillaceae | 0.0000000 |
| Zurich | B73 | rhizo | Planococcaceae | 0.0000000 |
| Zurich | B73 | rhizo | Pseudomonadaceae | 25.7652630 |
| Zurich | B73 | rhizo | Rhizobiaceae | 1.0453470 |
| Zurich | B73 | rhizo | Sphingobacteriaceae | 0.0000000 |
| Zurich | B73 | rhizo | Sphingomonadaceae | 0.3709773 |
| Zurich | B73 | rhizo | Streptomycetaceae | 0.0000000 |
| Zurich | B73 | rhizo | Weeksellaceae | 1.8244830 |
| Zurich | B73 | rhizo | Xanthomonadaceae | 0.3633009 |
| Zurich | B73 | root | Bacillaceae | 0.0000000 |
| Zurich | B73 | root | Chitinophagaceae | 0.0000000 |
| Zurich | B73 | root | Deinococcaceae | 0.0000000 |
| Zurich | B73 | root | Enterobacteriaceae | 13.5671680 |
| Zurich | B73 | root | Microbacteriaceae | 1.2066201 |
| Zurich | B73 | root | Micrococcaceae | 0.3605178 |
| Zurich | B73 | root | Moraxellaceae | 0.0000000 |
| Zurich | B73 | root | Nocardioidaceae | 0.0000000 |
| Zurich | B73 | root | Oxalobacteraceae | 4.5271340 |
| Zurich | B73 | root | Paenibacillaceae | 0.0000000 |
| Zurich | B73 | root | Planococcaceae | 0.0000000 |
| Zurich | B73 | root | Pseudomonadaceae | 19.2990819 |
| Zurich | B73 | root | Rhizobiaceae | 1.9816359 |
| Zurich | B73 | root | Sphingobacteriaceae | 0.0077196 |
| Zurich | B73 | root | Sphingomonadaceae | 1.1889132 |
| Zurich | B73 | root | Streptomycetaceae | 0.0000000 |
| Zurich | B73 | root | Weeksellaceae | 1.2172809 |
| Zurich | B73 | root | Xanthomonadaceae | 3.5980395 |
| Zurich | W22 | soil | Bacillaceae | 0.0000000 |
| Zurich | W22 | soil | Chitinophagaceae | 0.0000000 |
| Zurich | W22 | soil | Deinococcaceae | 0.0000000 |
| Zurich | W22 | soil | Enterobacteriaceae | 0.0345662 |
| Zurich | W22 | soil | Microbacteriaceae | 0.0000000 |
| Zurich | W22 | soil | Micrococcaceae | 0.2097291 |
| Zurich | W22 | soil | Moraxellaceae | 0.0000000 |
| Zurich | W22 | soil | Nocardioidaceae | 0.0000000 |
| Zurich | W22 | soil | Oxalobacteraceae | 0.5582531 |
| Zurich | W22 | soil | Paenibacillaceae | 0.0000000 |
| Zurich | W22 | soil | Planococcaceae | 0.0000000 |
| Zurich | W22 | soil | Pseudomonadaceae | 0.0000000 |
| Zurich | W22 | soil | Rhizobiaceae | 0.0268848 |
| Zurich | W22 | soil | Sphingobacteriaceae | 0.0000000 |
| Zurich | W22 | soil | Sphingomonadaceae | 0.0444825 |
| Zurich | W22 | soil | Streptomycetaceae | 0.0000000 |
| Zurich | W22 | soil | Weeksellaceae | 0.0714083 |
| Zurich | W22 | soil | Xanthomonadaceae | 0.1016998 |
| Zurich | W22 | rhizo | Bacillaceae | 0.1141118 |
| Zurich | W22 | rhizo | Chitinophagaceae | 0.0000000 |
| Zurich | W22 | rhizo | Deinococcaceae | 0.0000000 |
| Zurich | W22 | rhizo | Enterobacteriaceae | 0.2134681 |
| Zurich | W22 | rhizo | Microbacteriaceae | 0.0401601 |
| Zurich | W22 | rhizo | Micrococcaceae | 1.2586269 |
| Zurich | W22 | rhizo | Moraxellaceae | 0.0000000 |
| Zurich | W22 | rhizo | Nocardioidaceae | 0.0000000 |
| Zurich | W22 | rhizo | Oxalobacteraceae | 0.6575196 |
| Zurich | W22 | rhizo | Paenibacillaceae | 0.0000000 |
| Zurich | W22 | rhizo | Planococcaceae | 0.0000000 |
| Zurich | W22 | rhizo | Pseudomonadaceae | 12.1959143 |
| Zurich | W22 | rhizo | Rhizobiaceae | 0.7645875 |
| Zurich | W22 | rhizo | Sphingobacteriaceae | 0.0000000 |
| Zurich | W22 | rhizo | Sphingomonadaceae | 0.6621182 |
| Zurich | W22 | rhizo | Streptomycetaceae | 0.0000000 |
| Zurich | W22 | rhizo | Weeksellaceae | 0.7271068 |
| Zurich | W22 | rhizo | Xanthomonadaceae | 0.5548279 |
| Zurich | W22 | root | Bacillaceae | 0.0000000 |
| Zurich | W22 | root | Chitinophagaceae | 0.0000000 |
| Zurich | W22 | root | Deinococcaceae | 0.0000000 |
| Zurich | W22 | root | Enterobacteriaceae | 7.4779797 |
| Zurich | W22 | root | Microbacteriaceae | 0.4565680 |
| Zurich | W22 | root | Micrococcaceae | 0.2197740 |
| Zurich | W22 | root | Moraxellaceae | 0.0000000 |
| Zurich | W22 | root | Nocardioidaceae | 0.0000000 |
| Zurich | W22 | root | Oxalobacteraceae | 2.7327661 |
| Zurich | W22 | root | Paenibacillaceae | 0.0000000 |
| Zurich | W22 | root | Planococcaceae | 0.0000000 |
| Zurich | W22 | root | Pseudomonadaceae | 9.2871568 |
| Zurich | W22 | root | Rhizobiaceae | 0.8094188 |
| Zurich | W22 | root | Sphingobacteriaceae | 0.0000000 |
| Zurich | W22 | root | Sphingomonadaceae | 0.6755531 |
| Zurich | W22 | root | Streptomycetaceae | 0.0000000 |
| Zurich | W22 | root | Weeksellaceae | 0.7146973 |
| Zurich | W22 | root | Xanthomonadaceae | 1.8918109 |
| Sheffield | W22 | root | Bacillaceae | 2.1620284 |
| Sheffield | W22 | root | Chitinophagaceae | 0.0049149 |
| Sheffield | W22 | root | Deinococcaceae | 0.0000000 |
| Sheffield | W22 | root | Enterobacteriaceae | 0.0021627 |
| Sheffield | W22 | root | Microbacteriaceae | 0.3868906 |
| Sheffield | W22 | root | Micrococcaceae | 0.9893794 |
| Sheffield | W22 | root | Moraxellaceae | 0.0000000 |
| Sheffield | W22 | root | Nocardioidaceae | 0.0032314 |
| Sheffield | W22 | root | Oxalobacteraceae | 0.8706924 |
| Sheffield | W22 | root | Paenibacillaceae | 0.0840896 |
| Sheffield | W22 | root | Planococcaceae | 0.0165003 |
| Sheffield | W22 | root | Pseudomonadaceae | 0.5059968 |
| Sheffield | W22 | root | Rhizobiaceae | 0.0158535 |
| Sheffield | W22 | root | Sphingobacteriaceae | 0.0117742 |
| Sheffield | W22 | root | Sphingomonadaceae | 0.0000000 |
| Sheffield | W22 | root | Streptomycetaceae | 0.8482652 |
| Sheffield | W22 | root | Weeksellaceae | 0.0253353 |
| Sheffield | W22 | root | Xanthomonadaceae | 0.0102160 |
# count_sample_ASV <- all_phy_psmelt_iso_BX %>% filter(!Abundance %in% 0) %>% dplyr::select(OTU, rep, background, compartment, genotype, location, family) %>% group_by(OTU, background, compartment, genotype, location, family) %>% unique() %>% count()
#
# count_sample_ASV %>% filter(OTU %in% "ASV2230")
#
# count_sample_ASV_well_represented <- count_sample_ASV %>% filter(location %in% "Changins") %>% filter(compartment %in% "root") %>% filter(n > 2)
# represented_OTU <- count_sample_ASV_well_represented$OTU %>% unique()all_phy_psmelt_iso_BX_abundance %>% dplyr::select(-Strain) %>% unique()## # A tibble: 100,860 × 15
## OTU rep phylum family genus location background compartment bx1 WT
## <chr> <dbl> <chr> <chr> <chr> <fct> <fct> <fct> <dbl> <dbl>
## 1 ASV31 9 Proteo… Enter… Ente… Zurich W22 root 9.86 0
## 2 ASV4 1 Proteo… Pseud… Pseu… Zurich B73 rhizo 5.59 15.5
## 3 ASV31 11 Proteo… Enter… Ente… Zurich W22 root 14.7 0
## 4 ASV190 1 Proteo… Enter… Lell… Zurich W22 root 5.45 14.7
## 5 ASV190 7 Proteo… Enter… Lell… Zurich B73 root 2.56 14.3
## 6 ASV4 11 Proteo… Pseud… Pseu… Zurich B73 rhizo 9.09 14.2
## 7 ASV4 5 Proteo… Pseud… Pseu… Zurich W22 rhizo 0 13.8
## 8 ASV4 8 Proteo… Pseud… Pseu… Zurich B73 rhizo 10.4 13.7
## 9 ASV4 6 Proteo… Pseud… Pseu… Zurich B73 rhizo 4.28 13.4
## 10 ASV4 3 Proteo… Pseud… Pseu… Zurich B73 rhizo 13.3 12.3
## # ℹ 100,850 more rows
## # ℹ 5 more variables: BXcol <dbl>, log2FC <dbl>, WTbx1dif <dbl>,
## # WTbx1dif_zscore <dbl>, WTbx1dif_weigh_WT <dbl>Ranks of the isolates in the microbiome
all_phy_psmelt_rank <- all_phy_psmelt %>% dplyr::select(OTU, family, background, location, compartment, genotype, Abundance) %>% mutate(background_location_compartment_genotype = interaction(background, location, compartment, genotype, sep = "_")) %>% filter(!genotype %in% c("bx2", "bx6"))
all_phy_psmelt_rank_wide <- all_phy_psmelt_rank %>%
dplyr::select(-background, -location, -compartment, -genotype) %>%
group_by(OTU, family, background_location_compartment_genotype) %>%
dplyr::summarize(Abundance_mean = mean(Abundance)) %>%
pivot_wider(names_from = background_location_compartment_genotype, values_from = Abundance_mean)
all_phy_psmelt_rank_wide_r <- all_phy_psmelt_rank_wide %>% arrange(., desc(B73_Changins_root_WT))
all_phy_psmelt_rank_wide_r$rank_B73_Changins_root_WT <- c(1:nrow(all_phy_psmelt_rank_wide_r))
all_phy_psmelt_rank_wide_r <- all_phy_psmelt_rank_wide_r %>% arrange(., desc(B73_Changins_root_bx1))
all_phy_psmelt_rank_wide_r$rank_B73_Changins_root_bx1 <- c(1:nrow(all_phy_psmelt_rank_wide_r))
all_phy_psmelt_rank_OTU <- all_phy_psmelt_rank_wide_r %>%
dplyr::select(OTU, family, B73_Changins_root_WT, B73_Changins_root_bx1, rank_B73_Changins_root_WT, rank_B73_Changins_root_bx1) %>% mutate(rankdif_WTbx1 = rank_B73_Changins_root_bx1 - rank_B73_Changins_root_WT)
#write_rds(all_phy_psmelt_rank_OTU, "../Output/II_Field_soils/ll_phy_psmelt_rank_OTU.rds")
all_phy_psmelt_rank_OTU_iso <- left_join(all_phy_psmelt_rank_OTU, iso.tab, by = c("OTU" = "ASV"))
#write_rds(all_phy_psmelt_rank_OTU_iso, "../Output/II_Field_soils/all_phy_psmelt_rank_OTU_iso.rds")